Book Image

Neural Network Projects with Python

By : James Loy
Book Image

Neural Network Projects with Python

By: James Loy

Overview of this book

Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.
Table of Contents (10 chapters)

Predicting Diabetes with Multilayer Perceptrons

In the first chapter, we went through the inner workings of a neural network, how to build our own neural network using Python libraries such as Keras, as well as the end-to-end machine learning workflow. In this chapter, we will apply what we have learned to build a multilayer perceptron (MLP) that can predict whether a patient is at risk of diabetes. This marks the first neural network project that we will build from scratch.

In this chapter, we will cover the following topics:

  • Understanding the problem that we're trying to tackle—diabetes mellitus
  • How AI is being used in healthcare today, and how AI will continue to transform healthcare
  • An in-depth analysis of the diabetes mellitus dataset, including data visualization using Python
  • Understanding MLPs, and the model architecture that we will use
  • A step-by-step guide...