TensorFlow JS - Build Machine Learning Projects using JS

Learn TensorFlow.js and build Machine Learning projects using the famous client-side Javascript library.

4.00 (11 reviews)
Udemy
platform
English
language
Data Science
category
322
students
1.5 hours
content
Feb 2021
last update
$39.99
regular price

What you will learn

Learn about Scalar and Tensors.

Create Scalar and Tensors in TensorFlow JS.

Perform various Tensor operations.

Build a Linear Regression model from Scratch.

Build a Linear Regression model using a Sequential Model.

Build a Logistic Regression model using a Sequential Model.

Build an image classifier using MobileNet.

Description

Learn how to build Machine Learning projects using Javascript in this TensorFlow JS Course created by The Click Reader.

In this course, you will be learning about scalar as well as tensors and how to create them using TensorFlow.js. You will also be learning how to perform various kinds of tensor operations for manipulating and changing tensor values.

You will be performing a total of four Machine Learning projects while learning through this TensorFlow JS full course:

  1. Linear Regression from Scratch

You will be learning how to create a Linear Regression model from scratch using TensorFlow.js. You will be preparing the data, building the model architecture as well as training the model using a custom-made loss function as well as an optimizer.

  2. Linear Regression using a Sequential Model

You will be learning how to create a Linear Regression model using a Sequential Model with TensorFlow.js. You will be preparing the data, building the model architecture, training the model, viewing the change in the loss as well as build a multi-input regressor.

  3. Logistic Regression using a Sequential Model

You will be learning how to create a Logistic Regression model using a Sequential Model with TensorFlow.js. You will be preparing the data, building the model architecture, training the model as well as build a deep neural network classifier.

  4. Image Classification using MobileNet

You will be learning how to use a pre-trained model called MobileNet to build a dog breed classifier with TensorFlow.js.

By the end of this course, you will have learned how to build your own Machine Learning projects from scratch using TensorFlow JS.

Content

Introduction

Introduction
Setting up TensorFlow JS

Scalar and Tensors in TensorFlow.js

Introduction to Scalar and Tensors
Scalar and Tensors in TensorFlow JS
Different ways to create Tensors in TensorFlow JS
Performing Tensor operations in TensorFlow JS

Machine Learning Project: Linear Regression from Scratch

Linear Regression from Scratch using TensorFlow.js
Preparing the data
Building the Linear Regression model architecture
Training the Linear Regression model

Machine Learning Project: Linear Regression using Sequential Model

Linear Regression using Sequential model
Preparing the data
Building the Linear Regression model architecture
Training the Linear Regression model
Viewing the change in loss
Using multiple features as input

Machine Learning Project: Logistic Regression using Sequential model

Logistic Regression using Sequential model
Preparing the data
Building the Logistic Regression model architecture
Training the Logistic Regression model
Creating a Deep Neural Network Classifier

Machine Learning Project: Image Classification using MobileNet

Image Classification using MobileNet
Getting the image
Loading the MobileNet model
Predicting the dog breed

Screenshots

TensorFlow JS - Build Machine Learning Projects using JS - Screenshot_01TensorFlow JS - Build Machine Learning Projects using JS - Screenshot_02TensorFlow JS - Build Machine Learning Projects using JS - Screenshot_03TensorFlow JS - Build Machine Learning Projects using JS - Screenshot_04

Reviews

Gilbert
February 22, 2023
The Course only uses simulated data. This is impractical because machine learning involves data loading, preparation, before modeling. I would be decent to use and demonstrate the process of loading and preparing data for modeling. Additionally, the DOM / Console display is impractical, since most end users wouldn't have a effective means of interacting with this web technology.
José
February 22, 2021
The content is valuable but very poor, I expected more details or explanation about tensorflow like hoy/why but this is more like a demo tour. Also you should be very familiar with JavaScript and Machine Learning , otherwise you wouldn’t understahd anything.
Lucy
December 28, 2020
Les fichiers du dernier chapitre ne fonctionnent pas. Chrome affiche des erreurs. Les exemples ne sont pas intéressants.

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3538774
udemy ID
10/1/2020
course created date
10/7/2020
course indexed date
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