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Python Artificial Intelligence Projects for Beginners

Python Artificial Intelligence Projects for Beginners

By : Dr. Joshua Eckroth
2.2 (5)
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Python Artificial Intelligence Projects for Beginners

Python Artificial Intelligence Projects for Beginners

2.2 (5)
By: Dr. Joshua Eckroth

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
Table of Contents (7 chapters)
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Neural Networks

In this chapter, we will get an overview on neural networks. We will see what a simple shallow neural network is and get some familiarity with how they work. We will do this by trying to identify the genre of a song using a shallow neural network. We will also recall our previous work on the spam detector to use the neural network. Further on, we will take a look at larger neural networks, known as deep learning, and apply what is known as a convolutional neural network to identify handwritten mathematical symbols. Finally we will revisit the bird species identifier covered previously and use deep learning to produce a much more accurate identifier.

The topics that we will be covering in this chapter are as follows:

  • Understanding neural networks
  • Identifying the genre of a song using neural networks
  • Recalling our work on the spam detector to use neural...
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