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Python Artificial Intelligence Projects for Beginners : Get up and Running with Artificial Intelligence Using 8 Smart and Exciting AI Applications.

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This book demonstrates AI projects in Python covering modern techniques that make up the world of Artificial Intelligence. You will come across a variety of real-world projects on classifying data, text processing techniques, deep learning and neural networks.

Author(s): Eckroth, Joshua
Publisher: Packt Publishing Ltd
Year: 2018

Language: English
Pages: 155
City: Birmingham

Cover
Title Page
Copyright and Credits
Packt Upsell
Contributors
Table of Contents
Preface
Chapter 1: Building Your Own Prediction Models
Classification overview and evaluation techniques
Evaluation
Decision trees
Common APIs for scikit-learn classifiers
Prediction involving decision trees and student performance data
Summary
Chapter 2: Prediction with Random Forests
Random forests
Usage of random forest
Predicting bird species with random forests
Making a confusion matrix for the data
Summary
Chapter 3: Applications for Comment Classification
Text classification Machine learning techniquesBag of words
Detecting YouTube comment spam
Word2Vec models
Doc2Vec
Document vector
Detecting positive or negative sentiments in user reviews
Summary
Chapter 4: Neural Networks
Understanding neural networks
Feed-forward neural networks
Identifying the genre of a song with neural networks
Revising the spam detector to use neural networks
Summary
Chapter 5: Deep Learning
Deep learning methods
Convolutions and pooling
Identifying handwritten mathematical symbols with CNNs
Revisiting the bird species identifier to use images
Summary