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Course Outline
Introduction
- TensorFlow 2.x vs previous versions -- What's new
Setting up Tensoflow 2.x
Overview of TensorFlow 2.x Features and Architecture
How Neural Networks Work
Using TensorFlow 2.x to Create Deep Learning Models
Analyzing Data
Preprocessing Data
Building a Model
Implementing a State-of-the-Art Image Classifier
Training the Model
Training on a GPU vs a TPU
Evaluating the Model
Making Predictions
Evaluating the Predictions
Debugging the Model
Saving a Model
Deploying a Model to the Cloud
Deploying a Model to a Mobile Device
Deploying a Model to an Embedded System (IoT)
Integrating a Model with Different Languages
Troubleshooting
Summary and Conclusion
Requirements
- Programming experience in Python.
- Experience with the Linux command line.
Audience
- Developers
- Data Scientists
21 Hours