The Book of Why, written by Judea Pearl, explores why our artificial intelligence can perform complicated tasks by can't answer simple questions.
Machine learning, deep learning, and all other technologies that fit under the umbrella term “AI” should be considered only after you have well-defined goals and problems.
In The Big Nine, Amy Webb discusses the consequences of not fixing the broken state of artificial intelligence.
Applied machine learning, or applying artificial intelligence to practical applications, poses serious challenges. The book "Real World AI" explores these challenges in depth.
In "Artificial Intelligence: A Guide for Thinking Humans," computer scientist Melanie Mitchell lays out the good, bad and ugly of AI, deep learning and neural networks.
Machine Learning Algorithms, Second Edition, by Giuseppe Bonaccorso, is a good complement for those who have a solid knowledge of Python machine learning.
A highly underrated topic of discussion is how to choose the right keyboard to buy. Yes, it may seem like nothing important, but as we sit behind our...
We reviewed three books that provide a solid introduction to data science and machine learning.
The AI Advantage explores which which businesses are leveraging advances in artificial intelligence and what works and what doesn't in the field.
Linguistics for the Age of AI is a book that discusses the current challenges of natural language understanding and presents pathways to create language-aware AI systems.