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)

Breaking down the face recognition problem

Let's break down the face recognition problem into smaller steps and subproblems. That way, we can better understand what's going on under the hood of a facial recognition system. A face recognition problem can be broken down into the following smaller subproblems:

  • Face detection: Detect and isolate faces in the image. In an image with multiple faces, we need to detect each of them separately. In this step, we should also crop the detected faces from the original input image, to identify them separately.
  • Face recognition: For each detected face in the image, we run it through a neural network to classify the subject. Note that we need to repeat this step for each detected face.

Intuitively, this process makes a lot of sense. If we think of how humans recognize faces, we see that it is very similar to the process that we described...