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TensorFlow.js in 3 Hours

Video Description

Get up and running with Tensorflow.js in your browser

About This Video

  • Get up and running with Tensorflow.js quickly with practical real-world examples in a web browser
  • Tackle the most common Machine Learning problems using Tensorflow.js
  • Discover how to quickly include Deep Learning functionality in your own web applications in a web browser using pre-trained models

In Detail

In this course, you’ll learn how to use Tensorflow.js for a variety of the most popular Deep Learning tasks and use them in your own web browser.

You’ll start by learning how to classify images using commonly used Convolutional Neural Networks. And you’ll get up and running fast using a pre-trained model. Then you’ll explore yet another popular deep learning architecture called Long Short-Term Memory Recurrent Neural Network. This time you’ll classify text typed by a user in real time.

Moving on, you’ll work with audio data using a specific type of CNN. Then we’ll jump into methods to improve the results of our models by firstly looking at transfer learning. Here you’ll improve the performance of your model quickly by using a pre-trained model as a base and performing short, focused training.

By the end of this course, you’ll have the skills to use Tensorflow.js and train your own personal models using only a web browser.

Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/TensorFlow.js-in-3-Hours. If you require support please email: customercare@packt.com

Table of Contents

  1. Chapter 1 : Introduction to JavaScript and TensorFlow.js
    1. The Course Overview 00:06:20
    2. The Main Benefits of Using TensorFlow.js 00:03:27
    3. Running a Simple JavaScript Code in Your Web Browser 00:11:04
    4. Learning the Essential JavaScript Elements Part One – Variables, Functions, Loops, Conditions 00:18:49
    5. Learning the Essential JavaScript Elements Part Two – Objects, Methods, Libraries 00:03:45
    6. Getting Started with TensorFlow.js 00:02:47
    7. Let’s Practice JavaScript! 00:17:54
  2. Chapter 2 : Image Classification Using CNN
    1. Loading required CNN models 00:09:45
    2. Image Preparation 00:07:01
    3. Image Classification Using Loaded Models 00:03:53
  3. Chapter 3 : Real-Time Text Classification Using LSTM
    1. Loading Pre-Trained LSTM Model for Text Classification 00:11:22
    2. Text Preparation and Clean Up 00:05:10
    3. Putting It All Together to Classify Text in Real-Time 00:06:13
  4. Chapter 4 : Classifying Sounds with CNN
    1. Choosing the Right CNN Model and Getting It Ready for Classification 00:06:27
    2. Getting and Preparing a New Audio Sample 00:04:57
    3. Classify a Sound Sample Using CNN Model 00:04:16
  5. Chapter 5 : Using Transfer Learning to Get Better Results from Your CNN Model
    1. Create a New Model Based on Existing Pre-Trained CNN Model 00:04:09
    2. Getting and Preparing New Training and Testing Data 00:01:45
    3. Training and Testing the New Model 00:03:28
  6. Chapter 6 : Training Your Own CNN Model from the Ground Up
    1. Getting the Right Data 00:06:06
    2. Building a New CNN Model 00:12:08
    3. Training and Testing the Model 00:16:59
    4. Using Your New CNN Model to Classify New Data 00:02:50