Introduction
TensorFlow is a popular framework for working with machine learning. This module covers Keras, which is a higher-level and user-friendly API that's released as part of TensorFlow. For many scenarios, the level of abstraction provided by Keras gives you all the functionality you need, without the complexity of the lower-level concepts of TensorFlow.
At the end of this module, if you feel that you need more flexibility than Keras provides, then the fifth module of this learning path, Intro to Machine Learning with TensorFlow, shows how to reimplement a portion of the Keras code in this module using lower-level TensorFlow APIs.
Both this module and module five show how you can create a basic neural network using the Fashion MNIST dataset as a data source. You'll build a neural network that takes images of clothing as input, and then classifies them according to their contents, such as Shirt, Coat, or Dress.
For this module, we assume that you're comfortable with Python, but we don't assume any knowledge of Keras or TensorFlow.
Let's get started!
Learning objectives
- Learn to load and prepare data to be used in machine learning.
- Learn to specify the architecture of a deep learning neural network.
- Learn to train a neural network.
- Learn to make a prediction by using a neural network.
Prerequisites
- Knowledge of Python
- Basic knowledge about how to use Jupyter Notebooks