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 using this comprehensive guide * Enter the world of Artificial Intelligence, explore it, and create your own applications * Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want 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 will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. 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 In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data.
Artificial Intelligence, or simply AI, is being fueled by the ever-growing speed and power of computers and software. This power has increased to the extent that software can learn from experience, by constantly analyzing data and results until the software can make accurate interpretations of data and conditions on its own, thanks to its accumulated knowledge. This process is often referred to as machine learning. While the practical definition and ultimate capabilities of AI are debated, a number of industries have put AI to work and continue to invest very heavily in advanced development. Today, AI has synergies with many highly advanced technologies such as virtual reality, factory automation, robotics, self-driving cars, speech recognition, and predictive analytics. Deep learning is sometimes referred to in conjunction with phrases such as machine learning and neural networking.
Primarily intended for the undergraduate and postgraduate students of computer science and engineering, this text bridges the gaps in knowledge of the seemingly difficult areas of artificial intelligence and machine learning.
This book promises to provide the most number of case studies and worked out examples than any other of its genre. The text is written in a highly interactive manner which makes for an avid reading. More into the text, the contents are well placed that it takes off from the introduction to AI, which is followed by heuristics searching and game playing. The machine learning section begins with the basis of learning and the various association rule learning algorithms. Various types of learning like reinforced, supervised, unsupervised and statistical are also included with numerous case studies and application exercises. The well-explained algorithms and pseudo codes for each topic make this book useful for students.
Tomorrow begins right here as we embark on an enthralling and jargon-free journey into the world of computers and the inner recesses of the human mind. Readers encounter everything from the nanotechnology used to make insectlike robots, to computers that perform surgery, in addition to discovering the biggest controversies to dog the field of AI. Blay Whitby is a Lecturer on Cognitive Science and Artificial Intelligence at the University of Sussex UK. He is the author of two books and numerous papers.