π21 Best Artificial Intelligence Books to Learn AI:
Artificial Intelligence (AI) is a field that focuses on creating intelligent machines capable of performing tasks that usually require human intelligence, such as reasoning, speech recognition, and vision. Whether you’re a beginner or an advanced learner, these AI books will help you gain the skills needed to succeed in this growing field. Here is a curated list of the top AI books recommended by AI experts.
π1. Make Your Own Neural Network:
Author: Tariq Rashid
Edition: 1st Edition
Publisher: Independently Published
Overview: Learn the fundamentals of neural networks and how to create them using Python.
π2. Artificial Intelligence For Dummies:
Author: John Paul Mueller
Edition: 1st Edition
Publisher: For Dummies
Overview: A beginner-friendly guide that introduces AI concepts and their real-world applications.
π3. Machine Learning For Absolute Beginners:
Author: Oliver Theobald
Edition: 2nd Edition
Publisher: Scatterplot Press
Overview: Understand machine learning basics, from regression to neural networks, in simple terms.
π4. Superintelligence: Paths, Dangers, Strategies:
Author: Nick Bostrom
Edition: Unabridged Edition
Publisher: Audible Studios on Brilliance Audio
Overview: Explore the future implications of AI and how superintelligence could impact humanity.
π5. Artificial Intelligence: A Modern Approach:
Author: Stuart Russell & Peter Norvig
Edition: 3rd Edition
Publisher: Pearson
Overview: A comprehensive guide to AI theory and applications, ideal for students and professionals alike.
π6. Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning:
Author: James V Stone
Edition: 1st Edition
Publisher: MIT Press
Overview: Dive into deep learning algorithms with detailed mathematical explanations and practical examples.
π7. Life 3.0: Being Human in the Age of Artificial Intelligence:
Author: Max Tegmark
Edition: 1st Edition
Publisher: Knopf
Overview: Discusses how AI will transform society, ethics, and even the future of humanity.
π8. Deep Learning Illustrated:
Authors: Jon Kohn, Grant Beyleveld, and Aglae Basens
Edition: 1st Edition
Publisher: Pearson
Overview: A visually rich, beginner-friendly guide to the concepts of deep learning and its applications.
π9. Predictive Analytics For Dummies:
Authors: Anasse Bari, Mohamed Chaouchi, Tommy Jung
Edition: 1st Edition
Publisher: For Dummies
Overview: Understand the fundamentals of predictive analytics and its applications in business.
π10. Data Science from Scratch: First Principles with Python:
Author: Joel Grus
Edition: 1st Edition
Publisher: O’Reilly Media
Overview: Learn essential data science and machine learning concepts with hands-on Python code.
π11. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow:
Author: AurΓ©lien GΓ©ron
Edition: 2nd Edition
Publisher: O’Reilly Media
Overview: A hands-on guide to building intelligent systems using the most popular Python libraries.
π12. Applied Artificial Intelligence: A Handbook For Business Leaders:
Authors: Mariya Yao, Adelyn Zhou, Marlene Jia
Edition: 1st Edition
Publisher: Wiley
Overview: Learn how business leaders can harness AI and machine learning for business growth.
π13. Prediction Machines: The Simple Economics of Artificial Intelligence:
Authors: Ajay Agrawal, Joshua Gans, Avi Goldfarb
Edition: 1st Edition
Publisher: Harvard Business Review Press
Overview: A clear explanation of how AI’s predictive capabilities will change business models and industries.
π14. Human + Machine: Reimagining Work in the Age of AI:
Authors: Paul R. Daugherty, H. James Wilson
Edition: 1st Edition
Publisher: Harvard Business Review Press
Overview: A look at how AI is transforming business processes and creating new roles.
π15. Architects of Intelligence: The Truth About AI from the People Building It:
Author: Martin Ford
Edition: 1st Edition
Publisher: Packt Publishing
Overview: A collection of interviews with AI pioneers discussing the future of AI and its impact on society.
π16. Artificial Intelligence for Humans: Fundamental Algorithms:
Author: Jeff Heaton
Edition: 1st Edition
Publisher: Heaton Research
Overview: A practical guide to AI algorithms, including clustering, error calculation, and linear regression.
π17. HBRβs 10 Must Reads on AI, Analytics, and the New Machine Age:
Authors: Micheal E. Porter, Thomas H. Davenport, Paul Daugherty, H. James Wilson
Edition: 1st Edition
Publisher: Harvard Business Review Press
Overview: A collection of essential articles from Harvard Business Review on AI, analytics, and their business applications.
π18. Deep Learning (Adaptive Computation and Machine Learning series):
Author: Ian Goodfellow, Yoshua Bengio, Aaron Courville
Edition: 1st Edition
Publisher: MIT Press
Overview: The definitive guide to deep learning concepts, including deep architectures, optimization, and unsupervised learning.
π19. Python Machine Learning:
Author: Sebastian Raschka
Edition: 1st Edition
Publisher: Packt Publishing
Overview: Learn how to implement machine learning algorithms in Python, from beginner to advanced techniques.
π20. Deep Learning with R:
Author: François Chollet
Edition: 1st Edition
Publisher: Manning Publications
Overview: Learn deep learning techniques using the Keras library in R, with applications in computer vision and NLP.
π21. The Hundred-Page Machine Learning Book:
Author: Andriy Burkov
Edition: 1st Edition
Publisher: Andriy Burkov
Overview: A concise, yet comprehensive introduction to machine learning, suitable for both beginners and professionals.
πWho Can Learn Artificial Intelligence?
AI is a field accessible to anyone with an interest in technology. Whether you’re a student, developer, or business leader, there are various entry points to learn and apply AI, and the books listed above are an excellent resource for all levels.
πConclusion:-
Whether you’re starting your AI journey or looking to deepen your expertise, these books cover essential AI concepts, applications, and techniques. Start with beginner-friendly guides and progress to more advanced materials as you grow your skills. Happy learning!
