Creating a Responsive Web Design

This course was designed to teach you to create a web page that can adapt it’s layout to fit on any screen size, as well as on paper when printed.

Web design requires the coordination of HTML, CSS, and graphics in order to construct a layout and design that can respond to the varying needs of your websites visitors.

In this step-by-step course, we’ll cover every aspect of converting a design into a fully functioning web page. We’ll create navigation menus, style typography, format and position graphics, create CSS animations, import free web fonts from Google, as well adjust our layout to fit a wide range of screens and devices.

And for those new to HTML, CSS, or web graphics, we have a few lessons explaining the core fundamentals of each, so you’ll be able to work through the course without missing a beat.

Who is the target audience?

• Graphic Designers
• Web Designers
• UX Designers
• Front-End Web Developers
• Developers (looking to enhance their design sensitivities)
• Content Editors (responsible for HTML and CSS)

Basic knowledge

• Patience : )
• A text editor
• HTML5-enabled web browser
• Web-enabled phone or tablet (optional)
• Printer (optional)

What you will learn

• Strategize the HTML needed for a web design
• Create CSS rules to target specific HTML elements
• Work with web graphics (in HTML and CSS)
• Transform user experiences with CSS
• Adapt layouts for varying screen sizes
• Optimize a web page’s printing capabilities

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What is AI?

Although there is often lots of hype surrounding Artificial Intelligence (AI), once we strip away the marketing fluff, what is revealed is a rapidly developing technology that is already changing our lives. But to fully appreciate its potential, we need to understand what it is and what it is not!

Defining “intelligence” is tricky, but key attributes include logic, reasoning, conceptualization, self-awareness, learning, emotional knowledge, planning, creativity, abstract thinking, and problem solving. From here we move onto the ideas of self, of sentience, and of being. Artificial Intelligence is therefore a machine which possesses one or many of these characteristics.

However, no matter how you define it, one of AI’s central aspects learning. For a machine to demonstrate any kind of intelligence it must be able to learn.

When most technology companies talk about AI, they are in fact talking about Machine Learning (ML) — the ability for machines to learn from past experiences to change the outcome of future decisions. Stanford University defines machine learning as “the science of getting computers to act without being explicitly programmed.”

The science of getting computers to act without being explicitly programmed

In this context, past experiences are datasets of existing examples which can be used as training platforms. These datasets are varied and can be large, depending on the area of application. For example, a machine learning algorithm can be fed a large set of images about dogs, with the goal of teaching the machine to recognize different dog breeds.

Likewise, future decisions, refers to the the answer given by the machine when presented with data which it hasn’t previously encountered, but is of the same type as the training set. Using our dog breed example, the machine is presented with a previously unseen image of a Spaniel and the algorithm correctly identifies the dog as a Spaniel.

Training vs Inference

Machine Learning has two distinct phases: training and inference. Training generally takes a long time and can be resource heavy. Performing inference on new data is comparatively easy and is the essential technology behind computer vision, voice recognition, and language processing tasks.

Deep Neural Networks (DNNs), also known as deep learning, are the most popular techniques used for Machine Learning today.

Neural Networks

Traditionally, computer programs are built using logical statements which test conditions (if, and, or, etc). But a DNN is different. It is built by training a network of neurons with data alone.

DNN design is complicated, but put simply, there are a set of weights (numbers) between the neurons in the network. Before the training process begins, weights are generally set to random small numbers. During training, the DNN will be shown many examples of inputs and outputs, and each example will help refine the weights to more precise values. The final weights represents what has really been learned by the DNN.

As a result you can then use the network to predict output data given input data with a certain degree of confidence.

Once a network is trained, it is basically a set of nodes, connections, and weights. At this point it is now a static model, one that can be used anywhere needed.

To perform inference on the now static model, you need lots of matrix multiplications and dot product operations. Since these are fundamental mathematical operations, they can be run on a CPU, GPU, or DSP, although the power efficiency may vary.

Cloud

Today, the majority of DNN training and inference happens in the cloud. For example, when you use voice recognition on your smartphone, your voice is recorded by the device and sent up to the cloud for processing on a Machine Learning server. Once the inference processing has occurred, a result is sent back to the smartphone.

The advantage of using the cloud is that the service provider can more easily update the neural network with better models; and deep, complex models can be run on dedicated hardware with less severe power and thermal constraints.

However there are several disadvantages to this approach including time lag, risk of privacy, reliability, and providing enough servers to meet demand.

On-device inference

There are arguments for running inference locally, say on a smartphone, rather than in the cloud. First of all it saves network bandwidth. As these technologies become more ubiquitous there will be a sharp spike in data sent back and forth to the cloud for AI tasks.

Second, it saves power — both on the phone and in the server room — since the phone is no longer using its mobile radios (Wi-Fi or 4G/5G) to send or receive data and a server isn’t being used to do the processing.

Inference done locally delivers quicker results

There is also the issue of latency. If the inference is done locally, then the results will be delivered quicker. Plus there are myriad privacy and security advantages to not having to send personal data up to the cloud.

While the cloud model has allowed ML to enter into the mainstream, the real power of ML will come from the distributed intelligence gained when local devices can work together with cloud servers.

Heterogeneous computing

Since DNN inference can be run on different types of processors (CPU, GPU, DSP, etc.), it is ideal for true heterogeneous computing. The fundamental element of heterogeneous computing is the idea that tasks can be performed on different types of hardware, and yield different performance and power efficiency.

For example, Qualcomm offers an Artificial Intelligent Engine (AI Engine) for its top- and mid-tier processors. The hardware, combined with the Qualcomm Neural Processing SDK and other software tools, can run different types of DNNs, in a heterogeneous manner. When presented with a Neural Network built using 8-bit integers (known as INT8 networks), the AI Engine can run that on either the CPU or for better energy efficiency on the DSP. However, if the model uses 16-bit and 32-bit floating point numbers (FP16 & FP32), then the GPU would be a better fit.

The possibilities for AI augmented smartphone experiences are limitless

The software side of the AI Engine is agnostic in that Qualcomm’s tools support all the popular frameworks like Tensorflow and Caffe2, interchange formats like ONNX, as well as Android Oreo’s built-in Neural Network API. On top of that there is a specialized library for running DNNs on the Hexagon DSP. This library takes advantage of the Hexagon Vector eXtensions (HVX) that exist in top and mid-tier Snapdragon processors.

The possibilities for smartphone and smart-home experiences augmented by AI are almost limitless. Improved visual intelligence, improved audio intelligence, and maybe most importantly, improved privacy since all this visual and audio data remains local.

But AI assistance isn’t just for smartphone and IoT devices. Some of the most interesting advances are in the auto industry. AI is revolutionizing the future of the car. The long- term goal is to offer high levels of autonomy, however that isn’t the only goal. Driver assistance and driver awareness monitoring are some of the fundamental steps towards full autonomy that will drastically increase safety on our roads. Plus, with the advent of better natural user interfaces the overall driving experience will be redefined.

Wrap-up

Regardless of how it is marketed, Artificial Intelligence is redefining our mobile computing experiences, our homes, our cities, our cars, the healthcare industry — just about everything you can think of. The ability for devices to perceive (visually and audibly), infer context, and anticipate our needs allows product creators to offer new and advanced capabilities.

Machine Learning is redefining our mobile computing experiences

With more of these capabilities running locally, rather than in the cloud, the next generation of AI augmented products will offer better response times and more reliability, while protecting our privacy.

 

 

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Which is Best for Web Application Development—Dot Net, PHP, Python, Ruby, or Java

When we talk about the web application development technology, web browsers are flashing in our minds at very first moment. It is because web browsers can talk in terms of HTTP or web-sockets with the Internet.

Supports of Web Browsers

Moreover, web browser technologies are growing rapidly and expanding its supports for new programming languages that we never think of it. Mobile web browsers are behaving differently, and many web services work on mobile platforms with low-level native web browsers like WebView and APIs to give user interface.
The mobile web is hardly depending on de-facto standard desktop web technologies and leave enough room for diversity in web development technologies and frameworks.

Emerging Web Application Development Technologies

Therefore, we cannot rely on traditional Webs Application Development technologies such as PHP and Java, as server-side scripting languages, Ruby, and Python as standard web programming platforms, and .NET as emerging open source from a large proprietary software developer community of Microsoft.

We have to think of emerging scripting languages and frameworks such as JavaScript as full-fledged front-end and backend script, jQuery as a substitute of JavaScript in mobile web programming, Scala against Ruby, Elixir with Phoenix framework, Clojure with Datomic database, Haskel for serious functional programming, and Rust as a good alternative to it.
Node.js, Angular.js, Go, Dart, etc. are few names, which are gaining ground in the list of web development technologies. Therefore, sticking with one or two Web Application Development technologies for varying nature, size, and types of projects seems fatal attitude for the web programmers.

Particularly, for those programmers who have to traverse deep ocean of job market and career development in the stiffly competitive world of developers.
However, due to space constraints, we may discuss the traditional and standard web development technologies such as

• Dot Net
• PHP
• Python
• Ruby
• Java

All come with their pros and cons and appropriateness in modern contexts, particularly where mobile web is going to dominate, and some new other hardware technologies may wait to arrive on the Web-o-Sphere.

PHP Web Application Development

Hypertext Pre-Processor or PHP is a server-side scripting language developed with the intention to create powerful dynamic and interactive websites in the static website era.
It has rapidly gained momentum, and today nearly, 40% websites or web application in the world of the Internet is running with PHP in their source code. However, we can cite numerous reasons behind such immense popularity, but few are distinguished such as:

• It can easily embed into HTML code without requiring separate IDE
• It is with short learning curve and flexible so need frameworks to do organized coding and a lot of frameworks available for little to large-scale programming
• It is cross-platform and cross-browser compatible, as well as supports all existing web servers
• It has universal database supports, so integration of any database is possible with PHP
• It is open source and with huge open source community to support
• It is at the core of various open source software with great popularity such as WordPress, Joomla, Drupal, Magento, and so on
• Being the best PHP web application development service provider from India, we cater to hire php developers for different frameworks like Zend, Laravel, CakePHP and more we deliver responsive and cross-platform web applications using these framework with custom solutions.

ASP.NET Web Application Development

By nature, .NET is a framework, not a programming language. It is a product of the work of the proprietary giant Microsoft. It is supporting various Microsoft languages including VB & C#. The major part of .NET developer uses C# for desktop and mobile web development including cross-platform mobile applications.
Therefore, here we will discuss C# instead of ASP.NET framework. C# is a refined programming language with Object-Oriented Programming properties and follows MVC paradigm for rapid web application development.
ASP.NET offers flexibility and scalability that PHP can give only with various frameworks at different levels. C# has all good things in VB and C++ while support of Visual Studio with myriads of tools is great.

Visual Studio is shifting as open source and free platform gradually, and ASP.NET framework is decoupling from IIS to offer supports for a broad range of servers on the web.
PHP has various frameworks with the loyal community for each framework whereas .NET is a single framework with a comparatively huge community of developers. Therefore, you can collect a big team of desired skill sets easily for ASP.NET Web Application Development projects.

Python Web Application Development

Python in web developer community is considering as a general-purpose programming language for high-level designing and expressing concepts in a few lines of code. It has astounding readability, so if you know English, you can understand one-fourth of code written in Python.
Therefore, it is a good choice when a big team is working on a massive scale of the project, and a number of programmers have to read and code in a collaborative environment.
Python is supporting OOP and Functional Programming, as it is supporting multiple ways to create the structure and elements of programs for computing devices.
Its rapid prototyping and dynamic semantic capabilities are unbeatable so you can easily construct web applications by testing and importing vital functions.
Unfortunately, Python has a smaller community in comparison to PHP, NET and Java so find an expert developer is a tough job.

Ruby on Rails Web Application Development

Ruby is a high-level programming language, which just like PHP can be embedded into HTML easily. It is open source and pure OOP language for web programming as well as other purposes too.
Technically, it offers encapsulation of data methods within objects while doing OOP and developers can use a super advanced string as well as text manipulation techniques.
It enables developers to write multi-threaded apps using simple API, and it can easily connect to various databases including MySQL, Oracle, Sybase, DB2, and so on.
The more curious thing for Ruby is that it allows programmers to write external libraries in Ruby or C class languages. It also provides a mechanism for powerful string handling and advanced array class.
Some useful features of Ruby include better security coding, flexible syntax, and debugger to create a quality web application.
It is straightforward and easy for fresher to learn and code due to its easy and clean syntax. Of course, enormous learning resources are plus point for its vast developer community and fans.
Ruby has known framework, and it is Rails so sometimes it refers as Ruby on Rails (ROR) among its lovers.

Searching for Ruby on Rails Developers? Hire dedicated Ruby on Rails Developers team with Addon Solutions and meet Meet the world’s top RoR Programmers with affordable rate.

Java Web Application Development

 

Java is a platform-agnostic programming language for web and desktop applications and now used in Android for mobile application development. It is a pure Object-oriented language with strict conventions and typing.
Java is highly preferred programming language for enterprises for big scale projects for the web, intranet as desktop usage, and in modern M2M, IoT, and LBS, as embedded programming language.
It is because it offers high-end security coding, performance designing, and concurrency programming. It brings productivity for developers and eases their life with scalability and interoperability whenever needed.
The best thing for Java is that it is treating as the standard language in universities and courses so finding a Java developer is quite easy and with different levels of skill sets.
Therefore, just like PHP and ASP.NET languages and frameworks, Java is futuristic and give ‘Spring’ and ‘Play’ like programmer friendly frameworks to do rapid Web Application Programming.

Get in touch with Professional Java application development & integration services by Addon Solutions for your all in one requirements with our top multiple skills java developers for hire.

Conclusion:

If you have small-scale projects, selecting a single programming technology is a good option, but with large-scale projects, we cannot restrict with one and should go with a mix of multiple web programming languages, frameworks, and databases.
In big projects, sometimes finding developers with single skill sets is tough and we have to compromise by including multiple languages to serve different purposes.
Therefore, developers should learn more than one Web Application Development languages, and clients should select the web development companies with a mix of skill sets available as development resources.
If you think Addon Solutions as your dependable web development partner, you can access web programmers with expertise in various traditional and modern web development languages.

Click here To join us for more information, get in touch

Affiliate Marketing – Rollout Strategy Development

DESCRIPTION

Did you know that with very little to no investment required, you can be making an income from the Internet as an Affiliate Marketer. Are you interested in learning how? This course gives you a great start to building a new monthly income stream for yourself. Through this course, you will learn:

• How and where to start making money almost immediately selling 3rd party products
• Ways you can use Amazon to earn revenue for yourself as an affiliate
• My recommended top 10 Affiliate Marketing bulletin board sites where you can find quality products to promote and earn income
• How to sell your services online through affiliate sites where others help you find consulting engagements
• How you can put your own teams together to propose on and complete projects that you can take an overriding commission on for every hour your teams work
• How to build your own online affiliate programs so other people are selling your products
• Why you have made an income on day one just by starting a home business

I personally have been making my own income as a consultant and an online entrepreneur since before the year 2000. Except for a short period since the late 90’s, I have not worked as an employee for anyone – all of my income has come from my own entrepreneurial efforts. I have a lot of knowledge in Internet marketing in general and affiliate marketing online and I am looking forward to beginning to share it with you through this course – so come join me. Let me help you get started.

See you on the inside!  – Dan

BASIC KNOWLEDGE

All that is required is a desire to earn an extra income online.

WHAT YOU WILL LEARN

Through this course, you will learn how to select and implement Affiliate Marketing strategies for your new online business.

You will also gain an understanding as to what it takes to build an affiliate marketing program for one’s own products and services should you desire to take the path of building your own affiliate base.

 

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CompTIA IT Fundamentals; FC0-U51. The Total Course

DESCRIPTION

Welcome to the IT Fundamentals; FC0-501. The Total Course from Mike Meyers, Scott Jernigan, and Total Seminars.

Be your own Geek. This course is for everyone who has had to call a Help Desk or a Geek friend to help them with basic PC and mobile issues. You will learn about PCs, tablets, phones, networks, and Internet issues. You will also learn about security, safety, and preventative maintenance.

Learn how to:

•  Identify and understand basic computer components and what they do
•  Understand operating systems, data storage and sharing
•  Set up and configure a basic PC workstation
•  Work with applications and files
•  Handle basic software installation
•  Set up and configure a mobile device
• Connect to networks and the Internet
•  Identify/prevent basic security risks
•  Identify compatibility issues
•  Understand safety and preventative maintenance of computers

This course covers everything you need to know to pass the CompTIA IT Fundamentals Certification FC0-U51 exam. The first goal of the course is to help users better understand, set up, configure, and troubleshoot PCs and mobile devices. The process will prepared you to pass the CompTIA IT Fundamentals exam.

The course covers all the CompTIA IT Fundamentals FC0-U51 objective domains:

1.0 Software

2.0 Hardware

3.0 Security

4.0 Networking

5.0 Basic IT Literacy

The Total IT Fundamentals Course covers everything you need to know to be your own PC, mobile, network, and security Geek.

Who is the target audience?

• This course is for EVERYONE who uses PCs and mobile devices.
• CompTIA has a certification for IT Fundamentals (FC0-U51) but the course will help any user better understand the technology they use every day.

BASIC KNOWLEDGE

• Basic user of PCs, mobile devices, the Internet and networks.
• There are no specific prerequisites as the course covers all the topics in detail.

WHAT YOU WILL LEARN

• The first and most important goal of this course is to help every PC and mobile device user to better understand setup, software installation and configuration, network connectivity, security issues and basic troubleshooting.
• By the end of the course you will better understand everything from file structure, to software installation, to WiFi connectivity and troubleshooting to overall setup, configuration and troubleshooting PCs and mobile devices.
• This course will help you prepare for and pass the CompTIA IT Fundamentals FC0-U51 Certification exam.

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CompTIA Cybersecurity Analyst CSA+ CS0-001. The Total Course

DESCRIPTION

Welcome to CompTIA Cybersecurity Analyst CSA+ CS0-001. The Total Course from Total Seminars and Brent Chapman.

This course covers everything you need to know to pass your CompTIA CSA+

Certification (CS0-001) Exam. The first goal of the course is to make you an outstanding cybersecurity analyst and in the process, make sure you are ready to pass the CompTIA exam.

The course covers all the CompTIA CSA+ CS0-001 Objective Domains:

1.0 Threat Management: 27%

2.0 Vulnerability Management: 26%

3.0 Cyber Incident Response: 23%

4.0 Security Architecture and Tool Sets: 24%

Topics include:

Threat and vulnerability management

Conducting an analyzing reconnaissance

Responding to network-based threats

Securing a corporate network

Cyber incident response

Determining the impact of incidents

Preparing the incident response toolkit

CSA+ provides substantial earnings potential

A career in information security analysis ranked seventh on U.S. News and World Report’s list of the 100 best technology jobs for 2017. According to the Bureau of Labor Statistics, the median pay for an information security analyst is $90,120 per year.

CSA+ certified skills are in-demand

Properly trained IT security staff who can analyze, monitor and protect cybersecurity resources are in high demand.  The U.S. Bureau of Labor Statistics (BLS) predicts that information security analysts will be the fastest growing overall job category, with 37 percent overall growth between 2012 and 2022.

Follow the CompTIA Cybersecurity Certification Pathway

IT Fundamentals > A+ > Network+ > Security+ > CSA+ > CASP

Who is the target audience?

• This course is intended for anyone who is interested in a Cybersecurity position or looking to improve their security skills. The course will prepare you to pass the CompTIA CSA+ Certification Exam. It goes beyond certification and gives you the skills you need to be a better cybersecurity analyst.

BASIC KNOWLEDGE

• Basic familiarity with PCs and networks.
• There are no specific prerequisites as the course covers all the topics in detail.
• It is a good idea to have an understanding of CompTIA A+, Network+, and Security+ or to be certified in these topics. You can learn more about these certifications from our Mike Meyers – Total Seminars CompTIA A+, Network+, and Security+ Certification courses on Simpliv.

WHAT YOU WILL LEARN

• This is a complete and comprehensive CompTIA CSA+ Certification (CS0-001) course. It is designed to prepare the student to be able to take and pass the Cybersecurity Analyst exam and become CompTIA CSA+ Certified.
• Learn skills to break into a career in information security analysis, which ranks 7th in the 100 best tech jobs for 2017, and is predicted to be the fastest growing overall job category between 2012-2022. Cybersecurity Analysts earn a median pay of $90,120.

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Raspberry Pi and the Internet of Things

DESCRIPTION

• Taught by a team of electrical engineers from Stanford and IIT Madras.

An Internet-Of-Things course for everyone – accessible yet serious, to take you from absolute beginner to a solid intermediate level – built around Home Automation using Raspberry Pi.

This is a course is for everyone. You need not be an electrical engineer, or an engineer at all. We explain all engineering or automation concepts from absolute scratch.

This is an Internet-of-Things course, not merely a Raspberry Pi course. This is important because we think too many courses end up becoming like manuals for the Raspberry Pi, or the Arduino, or some specific hardware device. This course is careful to generalize

The course takes you to a solid intermediate level. The objective is to get you to a point where if you imagine a really cool IoT application, you will be able to independently figure out how to implement it.

We focus on Home Automation using Raspberry Pi for our use-cases. This is so that you can immediately put it to use around the home (turn that music down without getting off the couch!)

As with all our courses, this one too is quirky. The examples are irreverent. Lots of little touches: repetition, zooming out so we remember the big picture, active learning with plenty of quizzes. There’s also a peppy soundtrack, and art – all shown by studies to improve cognition and recall.

What’s Covered:

Internet of Things : Sensors, Actuators, Microcontrollers, Arduino, Raspberry Pi, Physical Computing, Smart homes

Raspberry Pi 2 Model B Components, System on a Chip (SOC) , Input Output Interfaces, SD Card / Secondary Storage, Choice of Operating Systems, RISC/CISC Architectures, x86 vs ARM, Raspbian OS installation, Raspbian tour, Linux Shell commands overview, Installing softwares, Connecting to the Internet

Physical Computing: Sensors (Photoresistors, Ultrasonic sensors, motion sensors, temperature and humidity sensors), Relays, LEDs, Push buttons, Basics of circuit design, Ohm’s law, RC circuit, GPIO pins, Serial and Parallel interfaces, UART, SPI, I2C, Pulse Width Modulation (PWM), Python (RPi DOT GPIO), WiringPi, Node js (RPi-GPIO)

Home Automation projects: Measuring Distance, Measuring Light Intensity, Controlling switches with sensors, Controlling switches over local and external networks

Who is the target audience?

• Yep! Anyone who is interested in Internet of Things, Physical computing, hardware hacking and wants to get their hands dirty with real projects
• Yep! Non-engineers / Non-tech persons who are interested in home automation projects or Raspberry Pi
• Yep! People who are looking to understand the details of IoT and want to think of new startup ideas in the IoT space or work in this space
• Yep! Engineers who have book knowledge but want some help with practical application of electronics concepts

BASIC KNOWLEDGE

• No real prerequisites. Beginner level understanding of electric circuits and programming might help but its not mandatory
• If you intend to do the physical computing projects, go ahead and purchase a Raspberry Pi – but the course does give you advice on things you might need to get for your automation projects so you can wait to decide as well.

WHAT YOU WILL LEARN

• Understand what the internet of things and physical computing are
• Know their way around a Raspberry Pi
• Use the Raspberry Pi in Home Automation projects
• Think of different IoT applications and visualize the components needed to build them
• Do cool things like control switches in their home with their smartphone

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Complete iOS 11 Machine Learning Masterclass

DESCRIPTION

If you want to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course is for you. The Complete iOS Machine Learning Masterclass™ is the only course that you need for machine learning on iOS. Machine Learning is a fast-growing field that is revolutionizing many industries with tech giants like Google and IBM taking the lead. In this course, you’ll use the most cutting-edge iOS Machine Learning technology stacks to add a layer of intelligence and polish to your mobile apps. We’re approaching a new era where only apps and games that are considered “smart” will survive. (Remember how Blockbuster went bankrupt when Netflix became a giant?) Jump the curve and adopt this innovative approach; the Complete iOS Machine Learning Masterclass™ will introduce Machine Learning in a way that’s both fun and engaging.

In this course, you will:

• Master the 3 fundamental branches of applied Machine Learning: Image & Video Processing, Text Analysis, and Speech & Language Recognition
• Develop an intuitive sense for using Machine Learning in your iOS apps
• Create 7 projects from scratch in practical code-along tutorials
• Find pre-trained ML models and make them ready to use in your iOS apps
• Create your own custom models
• Add Image Recognition capability to your apps
• Integrate Live Video Camera Stream Object Recognition to your apps
• Add Siri Voice speaking feature to your apps
• Dive deep into key frameworks such as coreML, Vision, CoreGraphics, and GamePlayKit.
• Use Python, Keras, Caffee, Tensorflow, sci-kit learn, libsvm, Anaconda, and Spyder–even if you have zero experience
• Get FREE unlimited hosting for one year
• And more!

This course is also full of practical use cases and real-world challenges that allow you to practice what you’re learning. Are you tired of courses based on boring, over-used examples? Yes? Well then, you’re in a treat. We’ll tackle 5 real-world projects in this course so you can master topics such as image recognition, object recognition, and modifying existing trained ML models. You’ll also create an app that classifies flowers and another fun project inspired by Silicon Valley™ Jian Yang’s masterpiece: a Not-Hot Dog classifier app!

Why Machine Learning on iOS

One of the hottest growing fields in technology today, Machine Learning is an excellent skill to boost your your career prospects and expand your professional tool kit. Many of Silicon Valley’s hottest companies are working to make Machine Learning an essential part of our daily lives. Self-driving cars are just around the corner with millions of miles of successful training. IBM’s Watson can diagnose patients more effectively than highly-trained physicians. AlphaGo, Google DeepMind’s computer, can beat the world master of the game Go, a game where it was thought only human intuition could excel.

In 2017, Apple has made Machine Learning available in iOS 11 so that anyone can build smart apps and games for iPhones, iPads, Apple Watches and Apple TVs. Nowadays, apps and games that do not have an ML layer will not be appealing to users. Whether you wish to change careers or create a second stream of income, Machine Learning is a highly lucrative skill that can give you an amazing sense of gratification when you can apply it to your mobile apps and games.

Why This Course Is Different

Machine Learning is very broad and complex; to navigate this maze, you need a clear and global vision of the field. Too many tutorials just bombard you with the theory, math, and coding. In this course, each section focuses on distinct use cases and real projects so that your learning experience is best structured for mastery.

This course brings my teaching experience and technical know-how to you. I’ve taught programming for over 10 years, and I’m also a veteran iOS developer with hands-on experience making top-ranked apps. For each project, we will write up the code line by line to create it from scratch. This way you can follow along and understand exactly what each line means and how to code comes together. Once you go through the hands-on coding exercises, you will see for yourself how much of a game-changing experience this course is.

As an educator, I also want you to succeed. I’ve put together a team of professionals to help you master the material. Whenever you ask a question, you will get a response from my team within 48 hours. No matter how complex your question, we will be there–because we feel a personal responsibility in being fully committed to our students.

By the end of the course, you will confidently understand the tools and techniques of Machine Learning for iOS on an instinctive level.

Don’t be the one to get left behind. Get started today and join millions of people taking part in the Machine Learning revolution.

topics: ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection ios 11 swift 4 coreml vision deep learning machine learning neural networks python anaconda trained models keras tensorflow scikit learn core ml ios11 Swift4 scikitlearn artificial neural network ANN recurrent neural network RNN convolutional neural network CNN ocr character recognition face detection

Who is the target audience?

• People with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence
• People who want to pursue a career combining app development and Machine Learning to become a hybrid iOS developer and ML expert
• Developers who would like to apply their Machine Learning skills by creating practical mobile apps
• Entrepreneurs who want to leverage the exponential technology of Machine Learning to create added value to their business could also take this course. However, this course does assume that you are familiar with basic programming concepts such as object oriented programming, variables, methods, classes, and conditional statements

BASIC KNOWLEDGE

• Basic understanding of programming
• Have access to a MAC computer or MACinCloud website

WHAT YOU WILL LEARN

• Build smart iOS 11 & Swift 4 apps using Machine Learning
• Use trained ML models in your apps
• Convert ML models to iOS ready models
• Create your own ML models
• Apply Object Prediction on pictures, videos, speech and text
• Discover when and how to apply a smart sense to your apps

 

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Shopify Website development course in 2018

DESCRIPTION

In this course you will learn how to create a Stunning Ecommerce website using Shopify.

Shopify is easy and flexible online platform where you can start your own Ecommerce shop instantly with in a day. It’s provides you no. of good futures to increase the functionality of your website. By using Shopify you can sell any of your products online using social media like Facebook, Twitter, Pinterest, Google plus Etc.

In this course you will learn following topics:

1. Introduction to Shopify.

2. How to create your store with Shopify.

3. How to add products and collections

4. How manage products and collections

5. Shopify Theme installation and customization

6. Menu management.

7. Pages creation.

8. Managing Payment Gateways

9. Understanding Checkout Process

10. Legal Pages

11. Shopify Setting options

12. Adding analytics to your website.

BASIC KNOWLEDGE

Basic Knowledge of computer and internet.

WHAT YOU WILL LEARN

How to build a stunning Shopify Ecommerce website.

 

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