I am curious about Artificial Intelligence, So which are the books available in India on Artificial Intelligence?
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
1. Artificial Intelligence: A Modern Approach by Stuart J. Russell and Peter Norvig (2009): This textbook is widely regarded as the most comprehensive exploration of AI available, covering all facets from search algorithms, game playing machines, robotics to natural language processing. It also contains a wealth of code examples for readers interested in learning how to program their own AI applications.
2. The Elements of AI by Reaktor and the University of Helsinki (2018): This book offers an accessible entry point into studying artificial intelligence, machine learning and deep learning practices and provides an overview on various concepts such as convolutional networks, recurrent neural networks, supervised & unsupervised learning among others – without requiring any previous programming experience.
3. Reinforcement Learning: An Introduction by Richard S. Sutton and Andrew G. Barto (2018): Written by two leading researchers in the field of reinforcement learning this volume presents a unified treatment of machine learning methods drawn from neural networks, control theory, evolutionary computation and other areas – essentially making it one of the best books on reinforcement training available today!
4. Machine Learning Yearning-Technical Strategy for AI Engineers in the Era Of Deep Learning By Andrew Ng (2018): As part of his series on effective machine learning strategies this book looks at scenarios where data sets are limited or non-existent; which can occur when working with sensitive data like healthcare patient info; how to prioritize development efforts for maximum impact; ways for speedier outcomes through using transfer-learning techniques among other topics related specifically to applied deep learning engineering practises .
1. Artificial Intelligence: A Modern Approach by Stuart J. Russell and Peter Norvig (3rd Edition): This is a must-read for anyone wanting to learn about AI in India, with its comprehensive coverage of the field and modern theories. It is especially popular among those who are just starting out in the field, as it gives an introduction to algorithms which can be used to develop AI systems.
2. Speech and Language Processing by Dan Jurafsky and James H Martindale (2nd Edition): This book provides an extensive treatment of speech recognition, natural language understanding as well as natural language processing tools and techniques available today such as vector space models, probabilistic models like hidden Markov models and machine learning methods like artificial neural networks for language processing tasks. It also covers spoken dialogue systems for human-computer interaction purposes such as customer service or robotic assistants that can recognize speech commands in natural language applications.
3. Artificial Intelligence: Foundations of Computational Agents by David Littman (2nd Edition): This book focuses on the theory behind AI agents that operate in environments where elements interact dynamically with each other over time, allowing them to learn from their experience using reinforcement learning or evolutionary computation through genetic algorithms approached from a computational standpoint rather than philosophical one. From this perspective, readers gain insight into topics ranging from game theory to planning problems or knowledge representation systems through case studies like RoboCup soccer competition robots or multiagent autonomous cars navigating safely on roads while detecting traffic signals quickly enough with deep learning methods within dynamic changing situations similar to real life scenarios observed at intersections around us everyday that challenge our current technologies greatly even up against specialists trained extensively since childhoods!
4. Machine Learning: A Probabilistic Perspective by Kevin P Murphy (1st Edition): This comprehensive overview of machine learning offers both beginners and experienced practitioners an accessible introduction into probabilistic approaches used for data analysis today including graphical models for Bayesian networks; support vector machines.
There are many great Artificial Intelligence books available in India that can help you gain a greater understanding of the subject. Some of the most popular titles include:
1. Artificial Intelligence for Humans (Volume 1): Fundamental Algorithms by Jeff Heaton
2. Python Machine Learning: Unlock Deeper Insights into Machine Learning with this Vital Guide to Cutting-Edge Predictive Analytics by Sebastian Raschka and Vahid Mirjalili
3. Deep Learning in Python: Master Data Science and Machine Learning With Modern Neural Networks Written in Python, Theano, and TensorFlow by Lazy Programmer Inc.
4. Building Intelligent Systems: A Guide to Machine Learning Engineering – By Andriy Burkov
5. Adventures in Machine Learning: An Introduction to Reinforcement & Deep Q-Learning Using OpenAI Gym by Andrew Trask
The best Artificial Intelligence books in India depend on the reader’s level of expertise. Beginner-level readers may want to consider introducing themselves to the subject with “Artificial Intelligence: A Modern Approach” by Stuart J. Russell and Peter Norvig or “Artificial Intelligence: Foundations of Computational Agents” by David L. Poole and Alan K. Mackworth, both published in 2017. For readers interested in exploring more advanced AI concepts, “Deep Learning” by Ian Goodfellow et al (2016) is an excellent book full of detailed explanations and examples that are easily digested even for those without a PhD in computer science. Additionally, “AI Algorithms: An Introductory Course” by Mandar Mitragotri (2019) provides a comprehensive overview of popular AI algorithms such as Support Vector Machines, Decision Trees, Naïve Bayes Classifiers, etcetera with plenty of code examples to help you get started quickly on your own AI projects.