Description
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you
About This Book
- Step into the amazing world of intelligent apps The use of this comprehensive guide
- Enter the world of Artificial Intelligence, explore it, and create your own applications
- Work through simple yet insightful examples so we can get you up and running with Artificial Intelligence in no time
Who This Book Is For
This book is for Python developers who need to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It’ll also be useful for experienced Python programmers who wish to use Artificial Intelligence techniques in their existing technology stacks.
What You Will Learn
- Realize different classification and regression techniques
- Understand the idea that 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 The use of 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
In Detail
Artificial Intelligence is becoming increasingly more relevant in the modern world. By harnessing the power of algorithms, you’ll be able to create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more.
Starting with AI basics you can move on to discover ways to develop building blocks The use of data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents
- Introduction to Artificial Intelligence
- Classification and Regression The use of Supervised Learning
- Predictive Analytics with Ensemble Learning
- Detecting Patterns with Unsupervised Learning
- Building Recommender Systems
- Logic Programming
- Heuristic Search Techniques
- Genetic Algorithms
- Building Games with Artificial Intelligence
- Natural Language Processing
- Probabilistic Reasoning for Sequential Data
- Building A Speech Recognizer
- Object Detection and Tracking
- Artificial Neural Networks
- Reinforcement Learning
- Deep Learning with Convolutional Neural Networks