Beginning Machine Learning in the Browser Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js

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Free Download Nagender Kumar Suryadevara, "Beginning Machine Learning in the Browser: Quick-start Guide to Gait Analysis with JavaScript and TensorFlow.js"
English | ISBN: 1484268423 | 2021 | 196 pages | AZW3 | 7 MB
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental coding ideas.

Using JavaScript programming features along with standard libraries, you'll first learn to design and develop interactive graphics applications. Then move further into neural systems and human pose estimation strategies. For training and deploying your ML models in the browser, TensorFlow.js libraries will be emphasized.
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JavaScript in the Browser
.MP4, AVC, 1280x720, 30 fps | English, AAC, 2 Ch | 2h 20m | 666 MB
Instructor: Christian Wenz​

Most JavaScript-based applications run in the browser. This course will teach you everything about the browser DOM and to interact with and change elements on the current page.

What you'll learn

JavaScript can be used almost everywhere, but most of the time it runs in the browser. So let's see how that works! In this course, JavaScript in the Browser, you'll learn to interact with web pages using JavaScript. First, you'll explore the browser DOM and how to change everything on the page. Next, you'll discover event handling. Finally, you'll learn how to handle HTML forms with JavaScript.

When you're finished with this course, you'll have the skills and knowledge of JavaScript needed to work with the scripting language in a browser context.

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Machine Learning in JavaScript with TensorFlow.js
MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | 6 hours 41 minutes | 75 lectures | 2.22 GB
Genre: eLearning | Language: English​

Master machine learning with JavaScript and TensorFlowJS. Add artificial intelligence to websites, Node.js and web apps!

Interested in using Machine Learning in JavaScript applications and websites? Then this course is for you!
This is
the
tutorial you've been looking for to
become a modern JavaScript machine learning master in 2024.
It doesn't just cover the basics, by the end of the course you will have advanced machine learning knowledge you can use on you resume. From absolute zero knowledge to master - join the TensorFlow.js revolution.
This course has been designed by a specialist team of software developers who are passionate about using JavaScript with Machine Learning. We will
guide you through complex topics
in a practical way, and reinforce learning with in-depth labs and quizzes.
Throughout the course we use house price data to ask ever more complicated questions; "can you predict the value of this house?", "can you tell me if this house has a waterfront?", "can you classify it as having 1, 2 or 3+ bedrooms?". Each example builds on the one before it, to reinforce learning in easy and steady steps.
Machine Learning in TensorFlow.js provides you with all the benefits of TensorFlow, but without the need for Python. This is demonstrated using web based examples,
stunning visualisations
and custom
website components
.
This course is fun and engaging, with Machine Learning learning outcomes provided in bitesize topics:
Part 1 - Introduction to TensorFlow.js
Part 2 - Installing and running TensorFlow.js
Part 3 - TensorFlow.js Core Concepts
Part 4 - Data Preparation with TensorFlow.js
Part 5 - Defining a model
Part 6 - Training and Testing in TensorFlow.js
Part 7 - TensorFlow.js Prediction
Part 8 - Binary Classification
Part 9 - Multi-class Classification
Part 10 - Conclusion & Next Steps
As a
bonus
, for every student, we provide you with
JavaScript and HTML code templates
that you can
download and use
on your own projects.

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