CourseFlix

Machine Learning in JavaScript with TensorFlow.js

6h 42m 20s
English
Paid

Learn how to use Machine Learning in JavaScript with clear steps and hands-on code. This course shows you how to build and train models in TensorFlow.js. You start with simple ideas and grow your skills with each lesson. You only need basic JavaScript to begin.

You work with real house price data. You ask direct questions like “can this model predict the price?” or “can it tell if the house has a waterfront?”. Each task builds on the last one, so you can follow the process with ease.

TensorFlow.js gives you Machine Learning tools in the browser. You do not need Python. You build small web demos, view model output, and test results as you code.

What You Learn

You move through short topics and practice with clear steps. Each part helps you build models, prepare data, and test ideas on your own.

  • Part 1 – Intro to TensorFlow.js

  • Part 2 – Install and run TensorFlow.js

  • Part 3 – Core concepts

  • Part 4 – Prepare data

  • Part 5 – Define a model

  • Part 6 – Train and test a model

  • Part 7 – Make predictions

  • Part 8 – Binary classification

  • Part 9 – Multi-class classification

  • Part 10 – Next steps

About the Author: Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

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#1: Introduction: What is TensorFlow.js?
All Course Lessons (52)
#Lesson TitleDurationAccess
1
Introduction: What is TensorFlow.js? Demo
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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