Course Outline


  • 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


Summary and Conclusion


  • Programming experience in Python.
  • Experience with the Linux command line.


  • Developers
  • Data Scientists
  21 Hours


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