English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 0h 57m | 162 MB
JavaScript developers can use the TensorFlow framework to create a machine learning (ML) project. This course introduces you to ML basics, and demonstrates how to set up and use TensorFlow to train a model and generate live results. Emmanuel Henri shows how to create a new project; how to work with different tensor types, variables, models, and layers; how to import a project and explore datasets; how TensorFlow executes model training; how to convert a saved model for the web; and more.
Topics include:
- Using TensorFlow
- Machine learning (ML) basics
- Creating a project with TensorFlow
- Working with tensors and variables
- TensorFlow ML operations
- Working with models and layers
- Importing a project
- Exploring datasets
- Training a model
- Using Python-based models in JS
- Converting SavedModel to web
Table of Contents
Introduction
1 Learning TensorFlow
2 Course prerequisites
Introduction and Setup
3 Introduction to TensorFlow
4 Differences between versions
5 Introduction to machine learning
6 A TensorFlow demo
7 Initial project creation with TensorFlow
TensorFlow Basics
8 Your first tensor
9 Tensors and variables
10 Operations or ops
11 Model introduction
12 Layers introduction
Exploration of a Full Project
13 Import example project
14 Exploration of the dataset
15 Exploration of the models and layers
16 Exploration of training the model
17 See the live example
Advanced Subjects
18 Use Python-based models in JS
19 Convert SavedModel to web
Conclusion
20 Next steps
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