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Python Artificial Intelligence Projects for Beginners

By : Dr. Joshua Eckroth

2.2 (5)

Buy this Book

Python Artificial Intelligence Projects for Beginners

2.2 (5)

By: Dr. Joshua Eckroth

Buy this Book

Overview of this book

Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress

Preface

Who this book is for

What this book covers

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Free Chapter

Building Your Own Prediction Models

Classification overview and evaluation techniques

Decision trees

Common APIs for scikit-learn classifiers

Prediction involving decision trees and student performance data

Summary

Prediction with Random Forests

Random forests

Predicting bird species with random forests

Summary

Applications for Comment Classification

Text classification

Detecting YouTube comment spam

Word2Vec models

Detecting positive or negative sentiments in user reviews

Summary

Neural Networks

Understanding neural networks

Identifying the genre of a song with neural networks

Revising the spam detector to use neural networks

Summary

Deep Learning

Deep learning methods

Identifying handwritten mathematical symbols with CNNs

Revisiting the bird species identifier to use images

Summary

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Summary

In this chapter, we covered a brief introduction to neural networks, proceeded with feed-forward neural networks, and looked at a program to identify the genre of a song with neural networks. Finally, we revised our spam detector from earlier to make it work with neural networks.

In the next chapter, we'll look at deep learning and learn about convolutional neural networks.