Build smart applications by implementing real-world artificial intelligence projects
Key Features:
- Explore a variety of AI projects with Python
- Get well-versed with different types of neural networks and popular deep learning algorithms
- Leverage popular Python deep learning libraries for your AI projects
Book Description:
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
What You Will Learn:
- Build a prediction model using decision trees and random forest
- Use neural networks; decision trees; and random forests for classification
- Detect YouTube comment spam with a bag-of-words and random forests
- Identify handwritten mathematical symbols with convolutional neural networks
- Revise the bird species identifier to use images
- Learn to detect positive and negative sentiment in user reviews
Who this book is for:
Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you're able to play around with code
Table of Contents
- Building Your Own Prediction Models
- Prediction with Random Forests
- Application for comment classification
- Neural Networks
- Deep Learning
