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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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