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All Projects → himanshurawlani → practical_intro_to_tf2

himanshurawlani / practical_intro_to_tf2

Licence: MIT license
Building an image classifier in TF2

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Jupyter Notebook
11667 projects

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tensorflowimage-classifiertensorflow-servingtensorflow-datasetstf-kerastensorflow-2

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Practical Introduction to TensorFlow 2.0

This repository introduces the new Tensorflow 2.0 in a practical way by building an image classifier which classifies 5 classes of flowers. It covers the following:

  1. Downloading and preprocessing data using TensorFlow Datasets
  • Checking out available datasets and their features
  • Downloading the dataset (tfds.load()))
  • Pre-processing the dataset
  • Visualizing the dataset
  1. Building and training an image classifier model using Keras high level API
  • Building a simple CNN in Keras
  • Visualising the model
  • Compiling and training the model
  • Training the model using data augmentation
  • Using TensorBoard inside notebooks
  1. Downloading and fine-tuning InceptionV3 pre-trained model
  • Downloading pre-trained model
  • Adding classification head
  • Training the classification head
  • Fine tuning the model
  1. Serving the trained model using TensorFlow Serving
  • Tensorflow Serving installation
  • Starting TensorFlow Serving
  • Making REST requests
  • Parsing the response

Read the Medium article explaining the above concepts in detail here.

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