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Saturday, February 29, 2020

Machine Learning in JavaScript with TensorFlow.js..94% off udemy coupon code

Udemy coupon.................................Updated for 2020!
Interested in using Machine Learning in JavaScript applications and websites? Then this course is for you!
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Machine Learning in JavaScript with TensorFlow.js

This is the tutorial you've been looking for to become a modern JavaScript machine learning master in 2020. 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.
Who this course is for:
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