Super Data Science: ML & AI Podcast with Jon Krohn avatar

Dexa/Super Data Science: ML & AI Podcast with Jon Krohn

Learn more
Published May 14, 2021

SDS 470: My Favorite Books — with Jon Krohn

Jon Krohn delves into the critical role of visual learning in deep learning mastery, sharing accessible resources like his educational series, and reveals the nonfiction and fiction books that have profoundly influenced his understanding of human nature and society, from "Sapiens" to "Cat's Cradle."
Episode Highlights
Super Data Science: ML & AI Podcast with Jon Krohn logo

Topics covered

Popular Clips

Episode Highlights

  • Visual Learning

    Visual learning plays a crucial role in understanding complex subjects like deep learning. highlights his book, "Deep Learning Illustrated," which uses over 100 hand-drawn illustrations and full-color mathematical equations to simplify the theory of artificial neural networks 1. This approach makes learning both engaging and accessible, especially for those who prefer visual aids.

    If you're into learning visually, then I can't help but mention my own book, Deep Learning Illustrated, which makes use of over 100 hand-drawn illustrations.

    ---

    He also recommends "Deep Learning" by Goodfellow, Bengio, and Courville, which, despite lacking code examples, serves as a comprehensive resource for deep learning enthusiasts 1.

       

    Mathematical Foundations

    Understanding the mathematical foundations is essential for mastering deep learning. emphasizes the importance of linear algebra, calculus, and probability theory, which are covered in his Machine Learning Foundation series available on YouTube 1. These resources aim to make complex mathematical concepts more accessible to learners without a strong math background.

    I've been working away on my Machine Learning Foundation series of lectures and video tutorials which detail the linear algebra, calculus, and probability theory.

    ---

    For those seeking a deeper understanding, his series offers a comprehensive guide to tackling advanced machine learning textbooks and academic papers 1.

Related Episodes