With the introduction of Artificial intelligence (AI) machines become increasingly capable of completing tasks and maximize the chance of successfully achieving their goals. Almost every industry across the globe is incorporating AI, from your smartphones to your cars to your home to your banking establishment. If you want to learn Artificial intelligence (AI) and fortify your foundation part then you are at the right place to explore best books to start with artificial intelligence.
Artificial Intelligence (AI) improves our lives by enhancing logical operations and nowadays it is essential and peculiar technology. Some of the applications of Artificial intelligence (AI) include expert systems, speech recognition, decision-making, visual perception, translating languages, process automation, predictive analysis, fraud detection, improving customer experience, etc.
Best Books to start with Artificial Intelligence (AI)
List of Artificial Intelligence Books |
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1. Make Your Own Neural Network
Make Your Own Neural Network is a popular book that takes you through the mathematics of neural networks step by step. It also helps you to create your Neural network (which is a key element of deep learning and artificial intelligence) using the Python programming language.
Author: Tariq Rashid
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2. Machine Learning: Indian Edition
“Machine Learning” is also considered as one of the best books on artificial intelligence and machine learning. This book focuses on the learning of the novices which covers the core topics like- Probability and statistics, artificial intelligence, Machine Learning theorems with pseudo-code summaries of their algorithms, and neural networks are all joined in a logical and coherent manner.
Author: Tom M. Mitchell
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3. TensorFlow in 1 Day: Make your own Neural Network
TensorFlow also helps you in deep learning. It provides you most authentic graph computations feature which will help in visualize and designed neural network. It also has both convolutions as well as Recurrent Neural network with detailed examples.
Author: Krishna Rungta
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4. Deep Learning (Adaptive Computation and Machine Learning series)
This useful Machine learning book offers mathematical, conceptual background, and relevant concepts in linear algebra, probability and information theory, optimization algorithms, and sequence modelling.
Also, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Author: Ian Goodfellow and Yoshua Bengio and Aaron Courville
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5. The Hundred-Page Machine Learning Book
The Hundred-Page Machine Learning Book is good for beginners. It gives a comprehensive guide to the fundamentals of machine learning. For experienced professionals, it gives practical recommendations from the author’s rich experience in the field of AI.
The book covers all major approaches to machine learning. They range from classical linear and logistic regression to modern support vector machines, boosting, Deep Learning, and random forests.
Author: Andriy Burkov
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6. Python Machine Learning
This book helps you in predictive analytics. It covers numerous methods to improve and optimize machine learning systems and algorithms.
Python Machine Learning book takes you to learn deeply- theory and practice of Python machine learning. Also, it extends your data science knowledge. It provides clear explanations, visualizations, and working examples, and all the essential machine learning techniques in depth.
Author: Sebastian Raschka Vahid Mirjalili
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7. Machine Learning for Designers
“Machine Learning for Designers” by Patrick Hebron is for UI and UX designers. It helps the designers to know how ML applications can affect the way of designing websites, mobile applications, and other software with real-world examples.
Author: Patrick Hebron
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8. Deep Learning with R
Deep Learning with R covers the powerful Keras library and its R language interface with practical examples. You’ll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models. This book has two parts- fundamentals of deep learning and deep learning in practice.
Author: J. J. Allaire
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9. Artificial Intelligence – A Modern Approach (3rd Edition)
A Modern Approach is one best book on artificial intelligence for beginners. One who interested in learning AI can go with this book which comprises of an excellent introduction to the theory and practice of artificial intelligence in modern technology.
Author: Stuart J. Russell and Peter Norvig
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10. Machine Learning for Dummies
This book is also good for novice and who want to start their career in Machine Learning. It covers all the basic concepts and theories of machine learning and how they apply to the real world. In order to perform data analysis, this book introduces little coding in Python and R.
Author: John Paul Mueller and Luca Massaron
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