In this course, you will learn:
- how to install TensorFlow and use it to build a simple deep learning model
- how to get TensorFlow up and running, instructor Adam Geitgey demonstrates how to create and train a machine learning model, as well as how to leverage visualization tools to analyze and improve your model.
- how to deploy models locally or in the cloud.
- What you should know
- Using the exercise files
1. Setting Up TensorFlow
- Install TensorFlow on macOS
- Install TensorFlow on Windows
2. TensorFlow Overview
- What is TensorFlow?
- Why is it called TensorFlow?
- Hardware, software, and language requirements
- The train/test/evaluation flow in TensorFlow
- Build a simple model in TensorFlow
3. Creating a TensorFlow Model
- Options for loading data
- Load the data set
- Define the model structure
- Set up the model training loop
4. Training a Model in TensorFlow
- Save and load trained models
- Visualize the computational graph
- Visualize training runs
- Add custom visualizations to TensorBoard
6. Using a Trained TensorFlow
- Export models for use in production
- Configure a new Google Cloud account
- Host your model in the cloud with Google Cloud
- Use a model in the cloud