How to Save and Restore Models with TensorFlow

In this course, you will learn how to save and restore models with TensorFlow. You can save models at any stage during training.

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How to Save and Restore Models with TensorFlow

Task List


We will cover the following tasks in 44 minutes:


Introduction

  • Development Environment
  • Quick look at a completed Jupyter Notebook

Introduction

Importing TensorFlow and the Dataset

  • Importing TensorFlow
  • Importing the Dataset
  • Subset of the Dataset
  • Plot an example
  • Reshape examples

Importing TensorFlow and the Dataset

Building a Model

  • Creating a model
  • Compiling the model
  • Model summary

Building a Model

Saving Checkpoints

  • Using model checkpoint callback.
  • Training the model.
  • Creating a new model and loading checkpoints.

Saving Checkpoints

Manually Saving Weights

  • Saving weights manually
  • Restoring weights manually

Manually Saving Weights

Saving Entire Models

  • The ‘save’ method
  • Loading models

Saving Entire Models

Watch Preview

Note: The actual session is completely hands-on where you interact with the software while watching the host's (Amit Yadav) instructions. You can preview the instructions here

Host: Amit Yadav


Amit Yadav

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Frequently Asked Questions


In Rhyme, all sessions are completely hands-on. You don't just passively watch someone else use the software. You use the software directly. While following the host's (Amit Yadav) instructions. Using the software is the only way to understand a software!
Nothing! Your host (Amit Yadav) has already installed all required software and configured all data in a virtual machine. You just join the session from a web-browser and start using the software immediately!
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