Machine Learning in JavaScript with TensorFlow.js
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 2022. 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.
Read more about the course
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
Watch Online Machine Learning in JavaScript with TensorFlow.js
| # | Title | Duration |
|---|---|---|
| 1 | Introduction: What is TensorFlow.js? | 05:35 |
| 2 | Course Overview | 06:33 |
| 3 | Machine Learning Concepts | 07:58 |
| 4 | Overview of Artificial Neural Networks | 10:09 |
| 5 | TensorFlow.js environments | 04:31 |
| 6 | Running TensorFlow.js in the browser | 05:53 |
| 7 | WebGL optimisations in TensorFlow.js | 05:18 |
| 8 | Running TensorFlow.js on Node.js | 13:42 |
| 9 | Review | 02:02 |
| 10 | TensorFlow.js APIs | 05:19 |
| 11 | What is a Tensor? | 11:44 |
| 12 | Tensor Math Operations & Ops API | 04:03 |
| 13 | Memory Management in TensorFlow.js | 08:32 |
| 14 | Review | 01:53 |
| 15 | Linear Regression | 06:37 |
| 16 | Reading data from CSV | 13:44 |
| 17 | Visualising the data | 07:29 |
| 18 | Preparing Features and Labels | 03:48 |
| 19 | Normalisation with TensorFlow.js | 07:50 |
| 20 | Splitting into Training and Testing data | 10:42 |
| 21 | Review | 01:53 |
| 22 | Introduction to Layers API | 05:37 |
| 23 | Creating Layers in TensorFlow.js | 10:25 |
| 24 | Inspecting a TensorFlow.js model | 05:53 |
| 25 | Compiling the model | 07:38 |
| 26 | Review | 01:38 |
| 27 | Introduction to Training and Testing | 04:33 |
| 28 | Training with model.fit | 05:28 |
| 29 | Visualising loss with tfjs-vis | 11:32 |
| 30 | Testing with model.evaluate | 06:14 |
| 31 | Training and testing: review & lab | 01:28 |
| 32 | Integrating TensorFlow.js with a UI | 19:02 |
| 33 | Saving and loading a model | 12:45 |
| 34 | Making Predictions | 07:48 |
| 35 | Visualising Predictions | 14:36 |
| 36 | Non-linear Regression | 13:38 |
| 37 | Prediction: review & labs | 02:07 |
| 38 | Introduction: Binary Classification | 05:21 |
| 39 | Visualising Classification Data | 19:25 |
| 40 | Preparing Multiple Features | 12:27 |
| 41 | Binary Classification Model | 05:19 |
| 42 | Visualising Classification with Heatmaps | 18:23 |
| 43 | Binary Classification Predictions | 05:14 |
| 44 | Binary Classification: Review & Lab | 02:20 |
| 45 | Introduction: Multi-class Classification | 08:05 |
| 46 | One hot encoding | 09:05 |
| 47 | Multi-class classification model | 04:38 |
| 48 | Visualising Multi-class Predictions | 13:06 |
| 49 | Multi-class prediction | 05:19 |
| 50 | Multi-class Classification: Review & Lab | 02:00 |
| 51 | Course Review | 08:10 |
| 52 | Next steps with TensorFlow.js | 07:51 |
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