Building and Deploying Deep Learning Applications with TensorFlow

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Free Online Course: Building and Deploying Deep Learning Applications with TensorFlow provided by LinkedIn Learning is a comprehensive online course, which lasts for 1-2 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from LinkedIn Learning. Building and Deploying Deep Learning Applications with TensorFlow is taught by Adam Geitgey.

Overview
  • Discover how to install TensorFlow and use it to create, train, and deploy a machine learning model.

Syllabus
  • Introduction

    • Welcome
    • 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
    • Train
    • Log
    • Save and load trained models
    5. TensorBoard
    • 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
    Conclusion
    • Next steps