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:
- 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
- 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
- Downloading and fine-tuning InceptionV3 pre-trained model
- Downloading pre-trained model
- Adding classification head
- Training the classification head
- Fine tuning the model
- 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.