Artificial Intelligence: Trends & Applications To Watch In 2020

For movie buffs, the work that the factory machines do in Charlie Chaplin’s 1936 classic, Modern Times, may have seemed too futuristic for its time. Fast forward eight decades, and the colossal changes that Artificial Intelligence is catalyzing around us will most likely give the same impression to our future generations. There is one crucial difference though: while those advancements were in movies, what we are seeing today are real.

A question that seems to be on everyone’s mind is, What is Artificial Intelligence? The pace at which AI is moving, as well as the breadth and scope of the areas it encompasses, ensure that it is going to change our lives beyond the normal. The thing with AI is that it can bring about developments in a very fundamental manner into the activities we are accustomed to carrying out in our daily lives, from the way we watch movies to how we learn.

The applications of AI are not limited to a single field or industry. A selection of just some of the sectors on which AI is making an unprecedented and irreversible impact:

  • Information Technology
  • EdTech Industry
  • Agriculture
  • Automobile
  • Manufacturing
  • Retail, and many more.

In this blog, let us examine a selection of 8 AI applications and 7 trends that show immense potential for changing the very manner in which our lives will be led in the future.

Just as we start, let me lead you into a very useful online course on Artificial Intelligence which will enhance your understanding of this technology, and is aimed precisely at those who want to learn Artificial Intelligence.

Click Here To Continue Reading

 

Artificial Intelligence and Big Data

Which factors help the organization to transform their business? Which technologies help them accomplish them to achieve their business goals? The answer should be Artificial Intelligence and Big Data.

Both Artificial Intelligence (AI) and Big Data are the two new emerging technologies of this modern tech-driven world. Artificial Intelligence has been in existence for a few decades, but Big Data has emerged just a few years back. These two technologies, when combined together can prove to be very powerful and help the organizations to analyze customer interests and provide them the best services.

Let us now understand both these technologies in brief.

Artificial Intelligence:

Artificial Intelligence is a branch of computer science which aims to create intelligent machines. It can also be understood as the ability of a computer to perform tasks that are similar to  those of human learning and decision making.

The applications provided by this technology are endless. This technology can be applied to many different sectors and industries. Looking at the benefits provided by this technology, many companies are willing to adopt AI technology into their business.

The fact that around 83% of businesses say that AI is now their strategic priority for their business is an indication of the extent to which AI is valued by businesses. The market of AI is also growing continuously. According to research firm Markets and Markets, the AI market will grow to a $190 billion industry by the year 2025.

Big Data:

Big Data refers to data with a huge size. Big Data is the term that describes a large amount of data – both structured and unstructured. This data is available from different sources such as from social media, blogs and comments, YouTube videos, email, etc.

Types of Big Data: Big Data can be found in three different terms:

  • Structured
  • Unstructured
  • Semi structured.

1) Structured: The data that can be stored, accessed and processed in the form of fixed format is known as structured data.

2) Unstructured: The data with an unknown form or structure is known as unstructured data.

3) Semi structured: Semi structured data contains both structured and unstructured data.

Artificial Intelligence and Big Data can work together

Both Artificial Intelligence and Big Data together are contributing to the growth of many businesses across the industries. Today, many organizations are relying on the meaningful insights obtained from Big Data for their business growth. To meet their business demands, organizations are considering  using Artificial Intelligence and Machine Learning techniques that help to stay ahead of the competition.

Organizations believe that AI will bring about a revolution into their organizational data. Artificial Intelligence involves Machine Learning techniques through which machines send or receive data and learn new concepts by analyzing the data. Big Data helps the organizations in analyzing their existing data and in drawing useful information from the same.

Combining AI and Big Data can be very advantageous for companies. As they both together provide meaningful insights immediately and accurately, this approach can be adopted across all industries.

Conclusion: We believe that this guide has been successful in providing you the information about both AI and Big Data technologies. These two technologies are working together to provide all the valuable aspects required for organizations to serve their customers in a better way and hence enhance their business.

If you are willing to learn these two technologies in detail then you can visit this link that contains all the valuable information required to master these technologies.

If you think some more information needs to be added to this blog, then please send your feedback in the comment section.

 

 

 

 

 

(AI) Artificial Intelligence -Digital Transformation Meetup

This Meetup aim is to discuss about Artificial Intelligence. It will be an ideal opportunity to explore critical areas of AI such as digital transformation, AI and deep learning, AI and cybercrime, AI as a tool for enforcing accountability, the various industries that could get impacted by AI, enterprise and process automation using AI, AI and costumer experience, AI’s role in messaging in the advertising, marketing and healthcare and other sectors, AI for the Cognitive Enterprise, and much more.

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Why You Need to Study Artificial Intelligence 2020

You’ve probably heard the terms Artificial Intelligence (AI) and Machine Learning (ML) recently in the news. It seems to be the new buzzwords, just like cryptocurrency not long ago. Bitcoin is not making headlines anymore, making people question, was it only a clickbait buzzword and is AI the same? What are these new technologies and why should we, the common people, the non-technical people, care? Reality is— our society is on the brink of a technological revolution, and Artificial Intelligence is at the core the Fourth Industrial Revolution which will fundamentally alter the way we live and work. It will affect all of us.

Leading technology giants Facebook, Google, Amazon are all excited about Artificial Intelligence. Google CEO Sundar Pichai emphasized in 2017 just how important AI is to the future of the company by saying:

“I’m really happy with how we are transitioning to an AI-first company. The Google Assistant is one of our first steps towards that future…Advances in machine learning are helping us make many Google products better… Beyond that, we continue to set the pace in machine learning and AI research.”

Even though we hear about it in the news, and see headlines, how many of us really know — what is AI? Why is it important? Let’s face it, there are not many people who truly understand what AI and ML are, it’s relatively new, but as it will have a huge impact on our lives in the future, we should aim to have at least a basic understanding of it. I would suggest to pay attention especially if you are still in the early days of your career. Chances are, it will deeply influence the future of work and your career as a result, no matter the industry you are in.

So — what is AI?

I have been really interested in everything related to the future and especially the technology that will shape it. But I have to admit, I also lacked a clear understanding of AI, even though I’ve known for a very long time about the massive importance of it.

During my University years, I always attended workshops around entrepreneurship and got the habit of going to one of the biggest tech conference in the Nordic, Slush, every year. Even though I studied business, I always tried to widen my perspective and educate myself in those topics that weren’t directly related to my studies. It is a shame business and technology studies are not integrated more, as it often is in the “real” world. So, I have been learning on my own, mostly because, well, I can. As I wrote in my previous article, it is up to us how we use the power that is access to unlimited information that is available thanks to the internet. I really find technology fascinating and over time, got over the limiting belief that only tech people need to know this stuff. I’m not a tech-head — what I am is a person of curiosity, ideas and dreams.

We cannot wait until someone or something (university) will give us the information we need, we need to educate ourselves. Taking matters in my own hands to learn about these concepts that are already major and will only get more significant in the future, I did what any other person would do — I Googled it.

Okay, so what about artificial intelligence?

By now you will have a solid foundation of knowledge in machine learning. However, this is only the tip of the iceberg – machine learning at its most basic provides a very limited form of artificial intelligence.

Advances in artificial intelligence are possible through ever more powerful algorithms – artificial or deep neural networks – that have additional layers of complexity (quite literally additional neurons).

These are the algorithms that are used to power sophisticated applications and tools. From image recognition to image identification, through to speech to text and machine translation, the applications of these algorithms are radically transforming our relationship with technology.

But you probably already knew that. The important question is how you actually go about doing it.

Well, luckily in many ways, if you know the core components of machine learning, more advanced elements of deep learning and artificial neural networks shouldn’t actually be as complex as you might at first think.

There are, however, a couple of considerations that become more important as you move deeper into deep learning.

Here are some of the results to what is AI:

· AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

· Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.

· Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.

· Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.

From this simple Googling experience, I already noticed that AI means different things to different people, and I had to go deeper in the attempt to better understand it.

Google is a good start. You can find many online courses and workshops organized all over the world if you live in a bigger city. Some of them might cost a lot of money since it really is a hot topic at the moment.

Free quality online education Finland style

Here’s where the Finnish education delighted me once again. I learned about an online course created by the University of Helsinki and Reaktor, called The Elements of AI. I saw many people in my professional network endorsing it on social media, so I didn’t hesitate for a moment to take this course.

I took the first module yesterday and I’m impressed. It’s mind blowing how this quality of teaching is free and accessible to anyone. The teaching material itself is amazing and equally importantly, the way it’s delivered is what the future of higher education can and should be.

The course is divided into 6 modules:

· What is AI?

· Solving problems with AI

· Real world AI

· Machine learning

· Neural networks

· Implications

Conversational AI Startups

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Introduction of Artificial Intelligence

In today’s world, technology is growing very fast, and we are getting in touch with different new technologies day by day.

Here, one of the booming technologies of computer science is Artificial Intelligence which is ready to create a new revolution in the world by making intelligent machines.The Artificial Intelligence is now all around us. It is currently working with a variety of subfields, ranging from general to specific, such as self-driving cars, playing chess, proving theorems, playing music, Painting, etc.

AI is one of the fascinating and universal fields of Computer science which has a great scope in future. AI holds a tendency to cause a machine to work as a human.

 

What is Artificial Intelligence?

Introduction to AI

Artificial Intelligence is composed of two words Artificial and Intelligence, where Artificial defines “man-made,” and intelligence defines “thinking power”, hence AI means “a man-made thinking power.”

So, we can define AI as:

“It is a branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions.”

Artificial Intelligence exists when a machine can have human based skills such as learning, reasoning, and solving problems

With Artificial Intelligence you do not need to preprogram a machine to do some work, despite that you can create a machine with programmed algorithms which can work with own intelligence, and that is the awesomeness of AI.

It is believed that AI is not a new technology, and some people says that as per Greek myth, there were Mechanical men in early days which can work and behave like humans.

Why Artificial Intelligence?

Before Learning about Artificial Intelligence, we should know that what is the importance of AI and why should we learn it. Following are some main reasons to learn about AI:

  • With the help of AI, you can create such software or devices which can solve real-world problems very easily and with accuracy such as health issues, marketing, traffic issues, etc.
  • With the help of AI, you can create your personal virtual Assistant, such as Cortana, Google Assistant, Siri, etc.
  • With the help of AI, you can build such Robots which can work in an environment where survival of humans can be at risk.
  • AI opens a path for other new technologies, new devices, and new Opportunities.

Goals of Artificial Intelligence

Following are the main goals of Artificial Intelligence:

  1. Replicate human intelligence
  2. Solve Knowledge-intensive tasks
  3. An intelligent connection of perception and action
  4. Building a machine which can perform tasks that requires human intelligence such as:
    • Proving a theorem
    • Playing chess
    • Plan some surgical operation
    • Driving a car in traffic
  5. Creating some system which can exhibit intelligent behavior, learn new things by itself, demonstrate, explain, and can advise to its user.

What Comprises to Artificial Intelligence?

Artificial Intelligence is not just a part of computer science even it’s so vast and requires lots of other factors which can contribute to it. To create the AI first we should know that how intelligence is composed, so the Intelligence is an intangible part of our brain which is a combination of Reasoning, learning, problem-solving perception, language understanding, etc.

To achieve the above factors for a machine or software Artificial Intelligence requires the following discipline:

  • Mathematics
  • Biology
  • Psychology
  • Sociology
  • Computer Science
  • Neurons Study
  • Statistics

Introduction to AI

Advantages of Artificial Intelligence

Following are some main advantages of Artificial Intelligence:

  • High Accuracy with less errors: AI machines or systems are prone to less errors and high accuracy as it takes decisions as per pre-experience or information.
  • High-Speed: AI systems can be of very high-speed and fast-decision making, because of that AI systems can beat a chess champion in the Chess game.
  • High reliability: AI machines are highly reliable and can perform the same action multiple times with high accuracy.
  • Useful for risky areas: AI machines can be helpful in situations such as defusing a bomb, exploring the ocean floor, where to employ a human can be risky.
  • Digital Assistant: AI can be very useful to provide digital assistant to the users such as AI technology is currently used by various E-commerce websites to show the products as per customer requirement.
  • Useful as a public utility: AI can be very useful for public utilities such as a self-driving car which can make our journey safer and hassle-free, facial recognition for security purpose, Natural language processing to communicate with the human in human-language, etc.

Disadvantages of Artificial Intelligence

Every technology has some disadvantages, and thesame goes for Artificial intelligence. Being so advantageous technology still, it has some disadvantages which we need to keep in our mind while creating an AI system. Following are the disadvantages of AI:

  • High Cost: The hardware and software requirement of AI is very costly as it requires lots of maintenance to meet current world requirements.
  • Can’t think out of the box: Even we are making smarter machines with AI, but still they cannot work out of the box, as the robot will only do that work for which they are trained, or programmed.
  • No feelings and emotions: AI machines can be an outstanding performer, but still it does not have the feeling so it cannot make any kind of emotional attachment with human, and may sometime be harmful for users if the proper care is not taken.
  • Increase dependency on machines: With the increment of technology, people are getting more dependent on devices and hence they are losing their mental capabilities.
  • No Original Creativity: As humans are so creative and can imagine some new ideas but still AI machines cannot beat this power of human intelligence and cannot be creative and imaginative.

ARTIFICIAL INTELLIGENCE SUMMIT:

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Simpliv, the learning platform, is organizing the AI Summit India on 18th November at Taj, Vivanta, Bangalore. This two-day summit will be an ideal opportunity to explore critical areas of AI such as digital transformation, AI and deep learning, AI and cybercrime, AI as a tool for enforcing accountability, the various industries that could get impacted by AI, enterprise and process automation using AI, AI and costumer experience, AI’s role in messaging in the advertising, marketing and healthcare and other sectors, AI for the Cognitive Enterprise, and much more.

10 Reasons why you should learn Artificial Intelligence

Introduction

Artificial Intelligence has revolutionized the way people think, learn, and work in various fields, from finance to healthcare and mobile apps. What’s more interesting is that AI plays more role in our daily lives than we can imagine. From Siri and Ok Google to various virtual player games and social media apps, AI is everywhere. It sure is the most happening topic in every business right now. It is the most wanted and exciting career domain right now in the market. Let us know what Artificial Intelligence is.

What is Artificial Intelligence?

Artificial Intelligence ( ) uses intelligent machines built in a way that they react like humans. The primary process involved in making these smart machines is to carry out decision making, which analysis and uses data available in an enterprise. It is similar to the human mind absorbing and synthesizing information and providing with the required decision.

1. Artificial Intelligence in Healthcare industry:

We are now in a digital age where everything could be implemented with the help of technology and Internet. Nowadays we get to see that a doctor can monitor and diagnose a patient from a remote location. This has reduced the necessity of being in person. Image the same way where the patient’s health condition is checked against predefined medications and algorithms prescribing a solution to the doctor. This would be a great success in the entire Healthcare industry. The current healthcare industry is completely dependant on the doctor’s sole knowledge and no supporting decision-making system is available to advise the treatments or the medication. It is completely coming up from the Doctor’s experience and decision. Imagine a condition where all the patient vitals and health records are pre-analyzed and a personalized treatment plan is produced for the doctor to review will change the entire treatment process.

2. Artificial Intelligence in responding to your emails:

If you have been using Gmail’s latest mobile application then responding to your emails would have been really easy and also exciting. So based on your email content, a predefined answer are already pre-populated as tags for you while responding back to the email. The latest version of Gmail mobile application has drastically reduced the turnaround time in terms of responding an email back. So the mobile applications are evaluating the emails now and giving us appropriate suggestions while writing back to the sender. Well, the possibilities are limitless and more importantly endless. So we got to wait for the future and see how it is going to affect the human interventions. The above list is a general observation of how Artificial Intelligence is already taking up its baby steps and improving the current processes. Well, the limitations are endless and one needs to understand to what extent it can be helpful. Involving and rebuilding the process by implementing Artificial Intelligence and Machine learning will be definitely the future and it makes sense to build the skill in this arena. A lot of possibilities are available where the implementations are not specific to an industry but this can be generalized.

3. Artificial Intelligence In Mobile World:

The smartphone nowadays is not only considered as a communication device anymore it can be called as your digital wallet and much more than that, even we can classify them as your personal assistants. Well, speaking about personal assistants, it is worth mentioning about “Siri”. It is one of the best examples of proper utilization of Artificial Intelligence and Machine learning. So based on your habits and interests “Siri” will be able to answer all your questions and provide valuable suggestions. This is already happening and this is the start of next wave of technology utilization. We have seen days where mobile devices didn’t have touchscreens and now we are in a digital age where the majority of the devices are touch screens. The next age of mobiles will be working on the voice commands which is nothing but “Siri”. This change will be huge and it will completely change the way people are using their mobile phones at the moment.

4. Artificial Intelligence in Smart Home Devices:

Based on your preferences what if your home environment is changed from time to time. Wondering whether this is possible or not? Well, it is definitely possible. In past few years, we have seen a lot of smart devices coming up in the market which works in line with our preferences. So basically based on your preferred patterns, the lighting in the house and temperature of the refrigerator and other household devices can definitely be monitored and eventually project optimum utilization settings as well. All of this is happening because of underlying machine learning and Artificial Intelligence built into these devices.

5. Artificial Intelligence in Automobile Industry:

If you are updated with the latest technology happenings then you wouldn’t have missed this at all. The concept of self-driving cars and autopilot features are in the news lately and big players like “Google” and “Tesla” are already in this arena. Have you ever imagined that you will be traveling in a car which doesn’t need a driver to take you from point A to point B. Well, this is not at all a dream anymore, a lot of test runs have gone through were the concept cars going to hit the road soon. This is definitely going to be the future in the automobile industry. A lot more research and development needs to happen within this area as we have to consider the safety and security aspect of the passengers. Well, we have to just wait and watch what is going to happen.

6. Artificial Intelligence in Music and Movie Recommendation services:

Who doesn’t like watching movies and listening to music right?
What if your next song or movie is recommended to you by a system based on your interests and browsing history? This would be pretty cool right!!!
Well, they are already few mobile applications that understand your choice of music and movies and recommend the same genre as a suggestion. This has been a massive success in terms of sales and promotions of various brands because the target market is available for the brands. The ads that you have seen on your browsers are also based on your previous activities. All of your activities are analyzed and a chain of recommendations are provided. With the help of the recommendations, it will definitely help the individuals to explore new options.

7. Artificial Intelligence in Retail industry:

This is going to be a huge game changer for all the retail companies because if they understand the purchase pattern and the requirements of their customers, they will definitely have to tailor their process to be the market leader. The Artificial Intelligence concept comes into the picture when the buying patterns are analyzed and understands the needs of the customer. The retail industry can gain huge profits by properly analyzing the customer needs vs buying the pattern and based on the consumption if the system could suggest:
Relevant coupons
Promote discounted offerings
Targeted marketing
Stocking the warehouses etc.

All of these subprocesses with definitely be improved and to be honest it will help the customer a lot. As of now, we are going towards a clash where the businesses are legally obligated that they are invading an individual privacy by closely evaluating their buying pattern and the products that they buy. In certain parts of the world, Amazon has started an offer called “Pantry” where they can select few products as essentials and they are automatically delivered to you on a periodic basis. Well, this is a perfect example for introducing the Artificial Intelligence into the process where a better operational and stocking activities are carried out.

8. Artificial Intelligence in Security Surveillance:

Safety and security are the important aspects and the basic needs of an individual or for an organization. The surveillance setup, i.e. security cameras monitoring important areas of the business is definitely a better idea. But watching too many screens for a very long time will be a boring job and ultimately we lose the option of attending the emergencies when there is a need. So what if there are predefined algorithms that are fed into the security cameras and make them more powerful. Based on the surveillance and the activities the system would be able to analyze and let us know whether the situation is actually a threat or not.  If it is a threat then it would immediately alert the human security officials associated with the business. If this sort of technology advancements are available right now then it would have made a positive impact on the security of the individuals and operationally the situation will be handled more efficiently.

9. Artificial Intelligence in Fraud Detection:

The fraud detection activity monitoring systems are actually a boom to the human kind where their money is protected by evaluating the transactions that they make. Have you ever received an email or a text message from your bank confirming the recent transaction activity was actually made by you or was it someone else who got hold of your card. Well, most of this transaction monitoring is carried out by the fraud detection team which is powered by AI. The transaction patterns of the individual, the usual withdrawal amount from the ATM and the frequency of the account logins. All of this data is stored and analyzed for suspicious activity.  For example: if you have never used your ATM card for years and all of a sudden you have started withdrawing money from your card then this would be definitely flagged as a fraud alert by the system. So the AI algorithms are developed by considering different scenarios and situations which will ultimately alert the users to be cautious about their belongings. The same technique can be expanded and further used in other industries as well.

10. Artificial Intelligence in Online Customer Support

Nowadays every business has a website for sure because it has been a need vs a luxury. With the rapid use of smartphones and internet, it has been evident that most of the customers are tending to get information via online interactions rather than phone interactions. So most of the websites have an online chat system which responds to your queries. Do you think that a real human is responding back to your queries all the time? Well, not all the time. To make sure the business is live and active 24/7 days businesses are opting for automated bots which actually does the same job as of a human. The responses are based on the content available on the website and the same is fed back to the customer based on his or her request. Well, this process is gaining more and more acceptance and the underlying logic is also going through a makeover where it can accommodate more requests and provide more accurate information. All of this is happening because of the rapid development of Natural Language Processing (NLP).

Rising Opportunities

Indeed reports that the number of AI-related job opportunities outranked the number of searches for AI engineer jobs. With increasing opportunities and using Artificial Intelligence in each sphere of life, the learning of this technology is more beneficial than we all think.

Some Resources to learn Artificial Intelligence

Learn Artificial Intelligence for Beginners

Let WIX, Artificial Intelligence (ADI) Build Your Website

Learn the Basic Fundamentals of Artificial Intelligence (AI) in Softwar…

 

 

 

 

7 Reasons Why You Should Learn Cyber Security

In the present scenario, Cyber Security is becoming one of the finest options to begin your career with. The prime reason is the growing demand of the experts across the globe since last few years. It is one of the Information Technology domains which are becoming more and more challenging. Due to the rapidly increasing cyber attacks across the globe, organizations are looking for the experts who can help them in tackling the same. Another fact is cyber security is a challenging domain and needs a lot of expertise for the professionals in order to eliminate attacks that are unauthorized in nature. Well, these are not the only reason that why Cyber Security has come up with excellent scope in recent years. There are of course, several other reasons too. Here is the list of top 7 reasons why you should learn cyber security this year.

In the current scenario, Cyber Security jobs are one of the most in-demand jobs to begin your career with. The Cyber Security industry has seen potential growth in the last few years and has created promising employment opportunities. Due to rapid and frequent cyber attacks across the globe, business, organizations and governments are looking for Cyber Security professionals that can prevent cyber attacks and tackle the existing ones. As a matter of fact, the need for Cyber Security professionals has outpaced the number of applicants. This makes it a career worth considering. Whether you have ever considered a career in cyber security or not, we have collected some of the most compelling reasons to think about getting involved in cyber security. So, put away your preconceptions and take a look at our list below. Cyber security is a fascinating profession, one that will put you at the heart of the technology that powers our modern world. From emulating hackers and building more secure applications to playing digital Sherlock Holmes and reconstructing crimes, cybersecurity covers a whole range of rewarding roles.

Throw away all your preconceptions of what a job in cyber security is like and ignore the usual Hollywood stereotype. Instead, focus on these seven reasons why cyber security will make a brilliant career choice:

Here are the top 7 reasons why you should learn Cyber Security

1. Good Salary Packages

Who doesn’t want a good salary package? Almost everyone and getting a good salary doesn’t hurt.

When it comes to building a career in Cyber Security, experience and knowledge are a must, however, starting a career with a good salary package is also a dream of many.

Therefore, a simple rule of demand and supply has been applied here. The demand for Cyber Security professionals is increasing day by day while the supply is considerably less.

So, employers are ready to pay higher salaries to Cyber Security professionals. This yet another reason why you should go ahead and learn Cyber Security.

As a coin has two sides, the world is filled with two kinds of people. One who uses internet optimally and positively to make the world a better place in terms of technology.

On the other hand, there are those who want to harm others by taking undue advantage of the internet.

Thus, to prevent themselves from online and cyber attacks, businesses and governments are looking for experts who can protect their systems from cyber criminals and hire the best human resource, they are willing to pay more.

By being a skilled Cyber Security professional with high demand, you can also negotiate your salary with any employer.

An increased Cyber Security demand has proved to be profitable for a lot of aspirants who had or have an interest in cyberspace.

Since the gap between the demand and supply of Cyber Security professionals is high, it has led to a higher pay rate for Cyber Security professionals.

2. Skills that no one knows

Cyber Security is a domain that simply introduces you with the skills that no one else can easily acquire. It is because of this reason also any young minds are paying a lot of attention o building career in this domain.

* White hat cyber security experts are familiar with many concepts about the network and other security which are very interesting to know
* They can simply make sure that professionals work with full satisfaction and have someone new to work on each day
* The job of a cyber security expert is not much complex but there is a lot to learn about the core networking, network security and so on
* Many professionals have already grabbed some of the best paying jobs because of no other reason than the skills they have acquired with time
* Professionals can easily learn the working of a number of gadgets and is thus a useful domain for those who have interest in this.

3. High Demand for Cyber Security Experts

The use of the Internet has increased considerably over the past decade. From ordering food to shopping, everything has become online.

While on one hand, this technological revolution has proved to be a boon, on the other hand, the internet has become more vulnerable to cyber attacks.

This has indeed created an infinite need for Cyber Security to prevent the web from online fraud and crime.

With technological advancement in the internet space, Cyber Security has become one of the most lucrative career options today and the demand for Cyber Security professionals is increasing day by day.

The demand for Cyber Security professionals is so high that they are getting hired at 12 times the rate than the rest of the related jobs and this is why you should learn Cyber Security.

Adding to the facts, the global demand for Cyber Security professionals is expected to rise to 6 million by the end of 2019 and a shortage of 1.5 million Cyber Security is expected to be witnessed.

4. Cyber Security is an Evergreen Industry

Gone were the days when Cyber Security was not a big deal. Today, in this ever-evolving technology era, the internet has become a priority for a majority of people.

Internet helps them to take care of their daily needs whether personal or professional. However, hackers across the world are simultaneously using the internet to fulfil their needs but in an unethical manner.

As cyber attacks are getting more prevalent these days, a continuous need for Cyber Security experts is also increasing. As a result of this, the job profile of a Cyber Security professional has become more stable than before.

You might be thinking that it is difficult to learn Cyber Security & cope up with the updates and trends of Cyber Security.

But the point is that there is nothing much that has changed in the Cyber Security domain, hence, you can easily begin your career as a Cyber Security professional.

5. Unlimited Career Growth Options

Cyber Security is expanding its horizon through various industries. This makes sure that is a perfect platform for growth in terms of career as well as learning opportunities.

These days, cyber attacks are getting smarter and faster. This arises the need for Cyber Security professionals to outsmart the hackers at a much more faster pace.

Businesses and governments are dependent on them for analysing & minimizing risk along with combating cyber attacks and preventing all types of vulnerabilities.

Tackling the cyber attacks are an outcome of continuous study, comprehensive research & optimal execution.

This proves that when you learn Cyber Security, you will be continuously knowing new things and gaining rich experience which is an add-on to your skill set.

6. Opportunities to work with High Profile Agencies

One of the best things about being a Cyber Security professional is that your chances of working with some of the biggest companies at many top positions in the world increases.

There is no restriction on the number of the organization that you can work with.

The demand for Cyber Security professionals has considerably increased across the globe. Thus, geographical hindrance is automatically cleared.

It has to be noted that the potential does not end here, experts in Cyber Security might also get the chance to work with some of the top-notch secret government & intelligence agencies like NSA, CBI etc along with Central Intelligence Agency, Department of Defense & various banks.

Sounds cool, isn’t it!

7. Learn “White-Hat” Hacking

With the expansion of Digitalization, internet marketing has become the first preference for almost everyone.

While on the positive side, it has created profitable opportunities for advertisers and marketers while providing promising career opportunities to a lot of people.

On the negative front, there has been an increase in the number of cyber crimes and attacks.

During the tenure of your Cyber Security certification, you will also get a chance to learn “white-hat” hacking.

If you learn Cyber Security & hacking, you will not only help yourself in building the right skill set but will also initiate an elevation in your resume value. This will make you the most wanted candidate from the employer’s point of view.

Useful Resources to Learn Cyber Security:

Web Hacking Secrets: How to Hack Legally and Earn Thousands of Dollars at HackerOne

Learn Identity and Access Management, Become an IIQ Developer

Constructs of Information Security Management System

Keep Hacking and Making Money at HackerOne

Ethical Hacking – Most Advanced Level Course

Complete Ethical Hacking & Penetration Testing for Web Apps

Computer Forensics and Incident Response

Ethical Hacking e Pentest com Kali Linux, Nmap e Metasploit

Ethical Hacking: How Hackers Uses DigiSpark to Hack Any PC

That’s all about the top 7 reasons why you should learn Cyber Security. There might be other reasons too but these are the best ones to consider it. Presently many colleges and universities are there which offer best programs for those who want to be a cyber security expert in future. It’s not just flexibility in this domain that is helping learners to keep up the pace but there are many other reasons too.

9 Reasons Why You Should Keep Learning Machine Learning

Machine Learning is an application of Artificial Intelligence. It allows software applications to become accurate in predicting outcomes. Machine Learning focuses on the development of computer programs, and the primary aim is to allow computers to learn automatically without human intervention.

Google says “Machine Learning is the future,” and the future of Machine Learning is going to be very bright. As humans become more addicted to machines, we’re witnesses to a new revolution that’s taking over the world, and that is going to be the future of Machine Learning.

More online businesses are integrating machine learning into their operations, with the bigger and established ones trailblazing the revolution.

Machine learning has brought myriad opportunities and improved strategies to help business owners foster customer relationships and get more profit and conversions.

If you haven’t fully leveraged the power of machine learning in your business, let me give you five reasons why you should do so now.

1. Machine learning helps increase your efficiency.

Can you imagine buying from the grocery store without having to wait in line to pay for your goods?

If you can’t, then you’d better prepared because that is now a reality.

Amazon, for one, has applied machine learning to make grocery shopping ultra-efficient for your customers through computer vision, sensor fusion, and deep learning algorithms.

Using the Amazon Go app, customers only need to open it, scan the QR code when they enter, pick their items, and confidently walk out of the store.

Amazon Go detects the items they take out from the shelves, automatically adds them into their virtual carts, and charges the bill into their Amazon accounts when they leave.

Such is a classic example of how machine learning can increase the efficiency of your business operations and processes, and help your customers, too.

While you can use pre-built machine learning technologies, you can also master how to develop them yourself.

The concept may sound complicated, but through the right machine learning course, you can invest in building machine learning technologies that suit your specific business needs.

2. You can understand your customers better.

Since the launch of automation, businesses have embraced customer-centeredness.

If you want to maintain a competitive edge over other businesses, you need to know what your customers need and give it to them.

If you fail to do so, you can lose your potential customers to your competitors.

Here is where machine learning plays a critical role.

Machine learning can analyze and organize patterns, trends, and data about your customers’ demographic profiles, choices and preferences, behaviors, and others.

Machine learning can get these data from online tools and mechanisms that you use, such as emails collected from sign-ups.

Such ability by machine learning enables you to know and understand your customers more quickly.

For instance, for your advertising campaigns on Google Adsense or other channels to be effective, they should be deeply targeted according to the mentioned data.

The more accurately you can understand your customers and their needs and wants, the more sharply you can target your ads.

3. You can personalize your marketing campaigns.

When customers feel that your offers are accurately aligned with their preferences — or personalized — they are more likely to patronize your business.

The question now becomes, how do you personalize your campaigns and customer shopping experience?

The answer is by using machine learning to build them based on the data gathered and analyzed, just like Flybits does.

Flybits is a context-as-a-service product that helps businesses provide hyper-personalized digital content and experiences for your customers.

With its easy user interface, your digital marketers can easily and instantly access internal and external data through cloud synchronization.

Its real-time mobile analytics allow you to customize your content and campaigns for your customers according to their location, weather, and others.

What’s more, Flybits ensures your customers’ data are safe and kept confidential. Your customers retain full ownership over their data as well.

Personalized campaigns are influential in increasing your conversions and sales, and machine learning help you create them.

4. Machine learning recommends products to your customers.

In line with personalizing your campaigns, machine learning can recommend products similar to what you previously viewed, purchased, or added to your cart.

Amazon is one company that uses machine learning to recommend similar products.

Machine learning picks up on the features of the items you previously searched, viewed, or bought, and creates algorithms from those data.

Amazon then personalizes its recommendations to you by stating your name and showing similar items.

It can also recommend to you similar items that other customers viewed or bought.

Let’s say you clicked on some Omine grey loafer sneakers.

Machine learning notes the features of the shoes, such as color, size, and style, and then shows you what other customers also bought.

In this way, they leverage social proof and fear of missing out (FOMO) to entice you to consider buying what other customers also liked (besides widening your range of options).

That said, machine learning helps you improve your sales and conversions significantly.

5. Machine learning helps to detect fraud.

The convenience that online payment systems offer, especially through mobile applications, has attracted both customers and businesses to transact and purchase online.

However, transmitting money online has also attracted cybercriminals and given them opportunities to execute fraudulent attacks.

Some businesses have implemented different cybersecurity measures but find that they need more to stop fraud.

If you’re experiencing the same problem, there’s fortunate news for you. Machine learning can now help strengthen businesses’ fraud detection system.

For instance, PayPal uses machine-learning mechanisms to catch suspicious and shady transactions and separate them from legitimate ones.

Machine learning further assists you by inspecting specific attributes among your data and develop standards as the basis for examining each transaction.

Machine learning, therefore, helps prevent malicious transactions from taking place even before you can complete them.

6) Learning machine learning brings in better career opportunities

According to a Tractica Report, AI driven services were worth $1.9 billion in 2016 and are anticipated to rise to $2.7 billion by end of 2017 of which 23% of the revenue comes through machine learning technology.

A report from TMR mentions that MLaaS (Machine learning as a Service) is expected to grow from $1.07 billion in 2016 to $19.9 billion by end of 2025.

Machine learning is the shining star of the moment. With every industry looking to apply AI in their domain, studying machine learning opens world of opportunities to develop cutting edge machine learning applications in various verticals – such as cyber security, image recognition, medicine, or face recognition. With several machine learning companies on the verge of hiring skilled ML engineers, it is becoming the brain behind business intelligence. Netflix announced prize worth $1 million to the first individual who could enhance the accuracy of its recommendation ML algorithm by 10%. This is a clear evidence on how significant even a slight enhancement is in the accuracy of recommendation machine learning algorithms to improve the profitability of Netflix. Every customer- centric organization is looking to adopt machine learning technology and is the next big thing paving opportunities for IT professionals. Machine learning algorithms have become the darlings of business and consumers so if you want to put yourselves somewhere in the upper echelon of software engineers then this is the best time to learn ML.

7) Machine Learning Engineers earn a pretty penny

The cost of a top, world-class machine learning expert can be related to that of a top NFL quarterback prospect. According to SimplyHired.com, the average machine learning engineer salary is $142,000.An experienced machine learning engineer can earn up to $195, 752.

8)  Machine Learning Jobs on the rise

You need a special kind of person to build a hammer, but once you build it, you can give it to many people who will use it to build a house.”

The major hiring is happening in all top tech companies in search of those special kind of people (machine learning engineers) who can build a hammer (machine learning algorithms). The job market for machine learning engineers is not just hot but it’s sizzling.

According to the popular job portal Indeed, the number of open machine learning jobs have been steadily rising from 2014 to  the onset of 2016, from 60 job postings per million to more than 100. The number of job postings jumped up to 150 postings per million by end of 2016. Indeed job trends report also reveals that the number of machine learning engineer job postings outstrip the number of searches for machine learning jobs – 100 million searches vs. 150 job postings.

A recent survey on the Indian job market found that there is a requirements of 4000 machine learning engineers in Bengaluru alone.

Here is a snapshot of the total number of machine learning jobs in US for IT professionals as of November 13, 2017 –

Machine Learning Engineer Jobs Positions on Glassdoor.com – 12000+

9) Machine learning is linked directly to Data Science

Machine learning appears as a shadow of data science. Machine learning career endows you with two hats, one is for a machine learning engineer job and the other is for a data scientist job. Becoming competent in both the fields makes an individual a hot commodity to most of the employers. It means that you can analyse tons of data, extract value and glean insight from it, and later make use of that information to train a machine learning model to predict results. In many organizations, a machine learning engineer often partners with a data scientist for better synchronization of work products. Furthermore, data scientist has been voted the Sexiest Job of 21st Century so one can get started as a data scientist specializing in Machine Learning and become more desirable to employers.

If these reasons ring a bell then you might be interested to get your start in machine learning career right now.

Are you ready to learn machine learning and land your dream job at one of the top tech companies? Share your personal approach, knowledge, and strategy in the comments below. Everyone has a different take on machine learning, and we want to know your thoughts.

Future of Machine Learning

Machine Learning can be a competitive advantage to any company be it a top MNC or a startup as things that are currently being done manually will be done tomorrow by machines. Machine Learning revolution will stay with us for long and so will be the future of Machine Learning.

Resources to learn Machine Learning

Learn Artificial Intelligence for Beginners

Machine Learning In The Cloud With Azure Machine Learning

Machine Learning Python: Regression Modeling

MACHINE LEARNING with Microsoft AZURE

Machine Learning with AWS

Machine Learning from scratch through Python

Machine Learning and Training Neural Network in MATLAB

Practical Deep Learning: Image Search Engine

DATA SCIENCE with MACHINE LEARNING and DATA ANALYTICS

Machine Learning and Data Science using Python for Beginners

Machine Learning using R and Python

Machine Learning Adv: Support Vector Machines (SVM) Python

Conclusion

We have studied the future and the algorithms of Machine Learning. Along with that, we have studied its application, which will help you deal with real life. Furthermore, if you have any queries, feel free to ask in the comments section.

 

 

What is data visualization? A definition, examples, and resources

Data visualization is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Patterns, trends and correlations that might go undetected in text-based data can be exposed and recognized easier with data visualization software.

Today’s data visualization tools go beyond the standard charts and graphs used in Microsoft Excel spreadsheets, displaying data in more sophisticated ways such as infographics, dials and gauges, geographic maps, sparklines, heat maps, and detailed bar, pie and fever charts. The images may include interactive capabilities, enabling users to manipulate them or drill into the data for querying and analysis. Indicators designed to alert users when data has been updated or predefined conditions occur can also be included.

Importance of data visualization

Data visualization has become the de facto standard for modern business intelligence (BI). The success of the two leading vendors in the BI space, Tableau and Qlik — both of which heavily emphasize visualization — has moved other vendors toward a more visual approach in their software. Virtually all BI software has strong data visualization functionality.

Data visualization tools have been important in democratizing data and analytics and making data-driven insights available to workers throughout an organization. They are typically easier to operate than traditional statistical analysis software or earlier versions of BI software. This has led to a rise in lines of business implementing data visualization tools on their own, without support from IT.

Data visualization software also plays an important role in big data and advanced analytics projects. As businesses accumulated massive troves of data during the early years of the big data trend, they needed a way to quickly and easily get an overview of their data. Visualization tools were a natural fit.

Visualization is central to advanced analytics for similar reasons. When a data scientist is writing advanced predictive analytics or machine learning algorithms, it becomes important to visualize the outputs to monitor results and ensure that models are performing as intended. This is because visualizations of complex algorithms are generally easier to interpret than numerical outputs.

The different types of visualizations

When you think of data visualization, your first thought probably immediately goes to simple bar graphs or pie charts. While these may be an integral part of visualizing data and a common baseline for many data graphics, the right visualization must be paired with the right set of information. Simple graphs are only the tip of the iceberg. There’s a whole selection of visualization methods to present data in effective and interesting ways.

Common general types of data visualization:

  • Charts
  • Tables
  • Graphs
  • Maps
  • Infographics
  • Dashboards

More specific examples of methods to visualize data:

  • Area Chart
  • Bar Chart
  • Box-and-whisker Plots
  • Bubble Cloud
  • Bullet Graph
  • Cartogram
  • Circle View
  • Dot Distribution Map
  • Gantt Chart
  • Heat Map
  • Highlight Table
  • Histogram
  • Matrix
  • Network
  • Polar Area
  • Radial Tree
  • Scatter Plot (2D or 3D)
  • Streamgraph
  • Text Tables
  • Timeline
  • Treemap
  • Wedge Stack Graph
  • Word Cloud
  • And any mix-and-match combination in a dashboard!

Why data visualization is important for any career

It’s hard to think of a professional industry that doesn’t benefit from making data more understandable. Every STEM field benefits from understanding data—and so do fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

While we’ll always wax poetically about data visualization (you’re on the Tableau website, after all) there are practical, real-life applications that are undeniable. And, since visualization is so prolific, it’s also one of the most useful professional skills to develop. The better you can convey your points visually, whether in a dashboard or a slide deck, the better you can leverage that information.

The concept of the citizen data scientist is on the rise. Skill sets are changing to accommodate a data-driven world. It is increasingly valuable for professionals to be able to use data to make decisions and use visuals to tell stories of when data informs the who, what, when, where, and how. While traditional education typically draws a distinct line between creative storytelling and technical analysis, the modern professional world also values those who can cross between the two: data visualization sits right in the middle of analysis and visual storytelling.

There are loads of free courses and paid training programs

There are plenty of great paid and free courses and resources on data visualization out there, including right here on the Simpliv website. There are videos, articles, and whitepapers for everyone from beginner to data rockstar. When it comes to third-party courses, however, we won’t provide specific suggestions in this article at this time.

Selenium Tutorials: Best Free Selenium Training Tutorials

This course talks in two hours about the different concepts of selenium using selenium ide. It discusses installation, usage, different selenium commands. explains locators, differences between verify and assert statement. It also talks about the limitations of selenium IDE. Selenium IDE is a firefox add on which is supported by firefox browser only. It is to be used only for record and playback of actions.

Who is the target audience?

Anyone interested in Selenium and Automation

Basic knowledge
  • Basic Manual Testing
What you will learn
  • Learn everything about Selenium IDE