Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you’ll learn about various algorithms that can be used to build Artificial Intelligence applications.
During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that’s based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide!
What You Will Learn
Realize different classification and regression techniques
Understand the concept of clustering and how to use it to automatically segment data
See how to build an intelligent recommender system
Understand logic programming and how to use it
Build automatic speech recognition systems
Understand the basics of heuristic search and genetic programming
Develop games using Artificial Intelligence
Learn how reinforcement learning works
Discover how to build intelligent applications centered on images, text, and time series data
See how to use deep learning algorithms and build applications based on it
Table of Contents
Chapter 1. Introduction to Artificial Intelligence
Chapter 2. Classification and Regression Using Supervised Learning
Chapter 3. Predictive Analytics with Ensemble Learning
Chapter 4. Detecting Patterns with Unsupervised Learning
Chapter 5. Building Recommender Systems
Chapter 6. Logic Programming
Chapter 7. Heuristic Search Techniques
Chapter 8. Genetic Algorithms
Chapter 9. Building Games With Artificial Intelligence
Chapter 10. Natural Language Processing
Chapter 11. Probabilistic Reasoning for Sequential Data
Chapter 12. Building A Speech Recognizer
Chapter 13. Object Detection and Tracking
Chapter 14. Artificial Neural Networks
Chapter 15. Reinforcement Learning
Chapter 16. Deep Learning with Convolutional Neural Networks
