Building Machine Learning Solutions with TensorFlow.js 2

سرفصل های دوره

In this course, you'll learn to use TensorFlow.js to build, train, and deploy machine learning and deep learning models to power client-side and server-side applications using the JavaScript language.

01. Course Overview

1. Course Overview

02. Introduction

1. Version Check

2. Introduction

3. Why TensorFlow.js-

4. TensorFlow.js Performance

5. TensorFlow.js Overview

6. Course Demo

7. Course Structure

03. Setting up TensorFlow.js Environment

1. Introduction

2. TensorFlow.js in Browser Using Script Tag

3. Demo- Running TensorFlow.js in Browser with Script Tag

4. TensorFlow.js in Browser Using Package Managers

5. Demo- Running TensorFlow.js in Browser Using NPM and Parcel

6. Demo- Exploring TensorFlow.js Backends

7. Demo- Running TensorFlow.js in Node.js

8. Summary

04. Understanding TensorFlow.js Core Concepts

1. Introduction

2. Tensor Overview

3. Demo- Working with Tensors

4. Basic Tensor Operations

5. Demo- Performing Basic Tensor Operations

6. Managing Memory with TensorFlow.js

7. Demo- Managing Memory with TensorFlow.js

8. Summary

05. Preparing Data for Machine Learning Model- Part 1

1. Introduction

2. Machine Learning Workflow

3. Toxicity Detection Use Case

4. Working with TFJS Data

5. Async JS Programming

6. Demo- Reading Data Using TFJS Data

7. Working with TFVis

8. Demo- Visualizing Data Using TFVis

9. Summary

06. Preparing Data for Machine Learning Model- Part 2

1. Introduction

2. Generating Features from Text

3. Demo- Generating TFIDF Features

4. Function Generator

5. Demo- Creating Feature Dataset Using Generators

6. Train Validation Test Split

7. Demo- Splitting Data into Train Validation and Test Datasets

8. Summary

07. Building, Training, and Evaluating Machine Learning Model

01. Introduction

02. Neural Network Overview

03. Building Neural Network Using Layers API

04. Demo- Building Neural Network Using Layers API

05. Training Model Using TensorFlow.js

06. Demo- Training Neural Network Model

07. Demo- Visualizing Training Performance

08. Demo- Evaluating Model Performance

09. Model Performance Metrics

10. Demo- Visualizing Model Performance Metrics

11. Demo- Running Training in Node.js

12. Summary

08. Saving and Loading Machine Learning Model

1. Introduction

2. Model Export Options

3. Demo- Exporting Trained Model

4. Load Model

5. Demo- Loading Trained TensorFlow.js Model

6. Summary

09. Predicting Using Trained Machine Learning Model

1. Introduction

2. Model Scoring

3. Demo- Predicting Using Trained TensorFlow.js Model

4. Materialize UI

5. Demo- Setting up Materialize UI

6. Demo- Integrate Steps with UI

7. TensorFlow.js Converter

8. Demo- Predicting Using Python Exported Model

9. Summary

10. Using Pre-trained Models with TensorFlow.js

1. Introduction

2. Transfer Learning with TensorFlow.js

3. Demo- Creating Features from Universal Sentence Encoder (USE) Model

4. Demo- Performing Transfer Learning on USE Encoded Features

5. Toxicity Detection Model

6. Demo- Using TensorFlow.js Toxicity Detection Model

7. Summary

11. Whats Next-

1. Taking Your Journey Forward

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تولید کننده: PluralSight