Learning TensorFlow with JavaScript
57mIntermediate2018-09-07
Authors
Emmanuel Henri
Executive with 20+ years of experience in programming and design
Course details
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.
Learning objectives
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
Learning objectives
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
Skills covered
TensorFlowNeural Networks and Deep LearningJavaScriptOracleGoogleArtificial Intelligence (AI)LearningProgramming LanguagesSoftware Development
Concepts
0. Introduction
- 01 - Learning TensorFlow
- 02 - Course prerequisites
1. Introduction and Setup
- 03 - Introduction to TensorFlow
- 04 - Differences between versions
- 05 - Introduction to machine learning
- 06 - A TensorFlow demo
- 07 - Initial project creation with TensorFlow
2. TensorFlow Basics
- 08 - Your first tensor
- 09 - Tensors and variables
- 10 - Operations, or ops
- 11 - Model introduction
- 12 - Layers introduction
3. 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
4. Advanced Subjects
- 18 - Use Python-based models in JS
- 19 - Convert SavedModel to web
Conclusion
- 20 - Next steps