Books on data science for me

For a programmer with a good grasp of Python and other programming languages but seeking a non-technical, figurative explanation of machine learning and AI, there are several excellent books that fit your criteria. Here are some recommendations:

"Deep Learning Illustrated" by Jon Krohn, Grant Beyleveld, and Aglaé Bassens:
- This book is known for its clear visual style and comprehensive look at deep learning. It uses beautiful illustrations and amusing analogies to make the theory behind deep learning accessible. It includes concrete, easy-to-follow examples with corresponding tutorial videos and code notebooks.[13]
"Deep Learning: A Visual Approach" by Andrew Glassner:
- This richly illustrated, full-color book offers visual and conceptual explanations instead of equations. It covers how deep learning systems work, including text generation, image classification, and game playing, making it ideal for those who prefer visual learning over mathematical details[14].
"You Look Like a Thing and I Love You: How AI Works and Why It's Making the World a Weirder Place" by Janelle Shane:
- Janelle Shane uses humor and quirky anecdotes to demystify AI. The book includes entertaining experiments and accessible language, making it a fun and informative read for those curious about the quirks of AI[1].
"Deep Learning Illustrated" by Jon Krohn, Grant Beyleveld, and Aglaé Bassens:
- This book is an approachable, practical, and broad introduction to deep learning. It is highly visual and includes lots of concrete examples, making it suitable for beginners and those looking to understand deep learning without diving into complex mathematics[13].
"Programming Machine Learning: From Coding to Deep Learning" by Paolo Perrotta:
- Although this book involves some coding, it takes a hands-on approach to machine learning, starting from scratch and building up to deep learning. It focuses on writing Python code without using libraries, helping you understand each line of code and the underlying concepts[2][6].

These books should provide you with a solid understanding of machine learning and AI through visual and figurative explanations, making the concepts more accessible and engaging.

Citations

[1] https://www.analyticsinsight.net/artificial-intelligence/non-technical-books-on-ai-and-machine-learning-for-beginners
[2] https://pragprog.com/titles/pplearn/programming-machine-learning/
[3] https://www.paralleldots.com/resources/blog/24-best-and-free-books-to-understand-machine-learning
[4] https://www.coursera.org/articles/machine-learning-books
[5] https://www.codemotion.com/magazine/ai-ml/10-books-on-artificial-intelligence-for-developers/
[6] https://www.amazon.com/Programming-Machine-Learning-Zero-Deep/dp/1680506609
[7] https://theaisummer.com/deep-learning-books-2022/
[8] https://www.reddit.com/r/learnmachinelearning/comments/13y4rzn/are_there_any_books_i_should_read_to_learn/
[9] https://www.superannotate.com/blog/computer-vision-books
[10] https://www.datarevenue.com/en-blog/what-is-machine-learning-a-visual-explanation
[11] https://www.reddit.com/r/MachineLearning/comments/81rel3/dwhich_is_your_favorite_nontechnical_book_from/
[12] https://mentorcruise.com/books/machinelearning/
[13] https://www.deeplearningillustrated.com
[14] https://www.amazon.com/Deep-Learning-Approach-Andrew-Glassner/dp/1718500726
[15] https://towardsdatascience.com/graph-machine-learning-an-overview-c996e53fab90
[16] https://link.springer.com/protocol/10.1007/978-1-0716-3195-9_1
[17] https://www.goodreads.com/list/show/24366.Best_machine_learning_books
[18] https://mlu-explain.github.io
[19] https://www.oreilly.com/library/view/practical-machine-learning/9781098102357/
[20] https://neptune.ai/blog/visualization-in-machine-learning