Book Image

Artificial Intelligence with Python - Second Edition

By : Prateek Joshi
Book Image

Artificial Intelligence with Python - Second Edition

By: Prateek Joshi

Overview of this book

Artificial Intelligence with Python, Second Edition is an updated and expanded version of the bestselling guide to artificial intelligence using the latest version of Python 3.x. Not only does it provide you an introduction to artificial intelligence, this new edition goes further by giving you the tools you need to explore the amazing world of intelligent apps and create your own applications. This edition also includes seven new chapters on more advanced concepts of Artificial Intelligence, including fundamental use cases of AI; machine learning data pipelines; feature selection and feature engineering; AI on the cloud; the basics of chatbots; RNNs and DL models; and AI and Big Data. Finally, this new edition explores various real-world scenarios and teaches you how to apply relevant AI algorithms to a wide swath of problems, starting with the most basic AI concepts and progressively building from there to solve more difficult challenges so that by the end, you will have gained a solid understanding of, and when best to use, these many artificial intelligence techniques.
Table of Contents (26 chapters)
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Constructing a multi-layer neural network

So, we enhanced our model from a few nodes to a single-layer, but we are still far away from 85 billion nodes. We won't get to that in this section either, but let's take another step in the right direction. The human brain does not use a single-layer model. The output from some neurons becomes the input for other neurons and so on. A model that has this characteristic is known as a multi-layer neural network. This type of architecture yields higher accuracy, and it enables us to solve more complex and more varied problems. Let's see how we can use NeuroLab to build a multi-layer neural network.

Create a new Python file and import the following packages:

import numpy as np
import matplotlib.pyplot as plt
import neurolab as nl

In the previous two sections, we saw how to use a neural network as a classifier. In this section, we will see how to use a multi-layer neural network as a regressor. Generate...