TensorFlow JS Build Machine Learning Projects using JS

TensorFlow JS – Build Machine Learning Projects using JS, available at $39.99, has an average rating of 4, with 26 lectures, based on 12 reviews, and has 326 subscribers.

You will learn about 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. This course is ideal for individuals who are Any developer looking to learn how to build, train and deploy Machine Learning models using Javascript. It is particularly useful for Any developer looking to learn how to build, train and deploy Machine Learning models using Javascript.

Enroll now: TensorFlow JS – Build Machine Learning Projects using JS

Summary

Title: TensorFlow JS – Build Machine Learning Projects using JS

Price: $39.99

Average Rating: 4

Number of Lectures: 26

Number of Published Lectures: 26

Number of Curriculum Items: 26

Number of Published Curriculum Objects: 26

Original Price: $199.99

Quality Status: approved

Status: Live

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.

Who Should Attend

Any developer looking to learn how to build, train and deploy Machine Learning models using Javascript.

Target Audiences

Any developer looking to learn how to build, train and deploy Machine Learning models using Javascript.

Learn how to build Machine Learning projects using Javascript in this TensorFlow JS Coursecreated 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.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome to the course!

Lecture 2: Setting up TensorFlow JS

Chapter 2: Scalar and Tensors in TensorFlow.js

Lecture 1: Introduction to Scalar and Tensors

Lecture 2: Scalar and Tensors in TensorFlow JS

Lecture 3: Different ways to create Tensors in TensorFlow JS

Lecture 4: Performing Tensor operations in TensorFlow JS

Chapter 3: Machine Learning Project: Linear Regression from Scratch

Lecture 1: Linear Regression from Scratch using TensorFlow.js

Lecture 2: Preparing the data

Lecture 3: Building the Linear Regression model architecture

Lecture 4: Training the Linear Regression model

Chapter 4: Machine Learning Project: Linear Regression using Sequential Model

Lecture 1: Linear Regression using Sequential model

Lecture 2: Preparing the data

Lecture 3: Building the Linear Regression model architecture

Lecture 4: Training the Linear Regression model

Lecture 5: Viewing the change in loss

Lecture 6: Using multiple features as input

Chapter 5: Machine Learning Project: Logistic Regression using Sequential model

Lecture 1: Logistic Regression using Sequential model

Lecture 2: Preparing the data

Lecture 3: Building the Logistic Regression model architecture

Lecture 4: Training the Logistic Regression model

Lecture 5: Creating a Deep Neural Network Classifier

Chapter 6: Machine Learning Project: Image Classification using MobileNet

Lecture 1: Image Classification using MobileNet

Lecture 2: Getting the image

Lecture 3: Loading the MobileNet model

Lecture 4: Predicting the dog breed

Lecture 5: Bonus Lecture

Instructors

The Click Reader
Teaching Data Science and Machine Learning

Rating Distribution

1 stars: 1 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 6 votes

5 stars: 3 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!