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Deep Learning

Deep Learning

Explore these advanced resources, spanning from in-depth deep learning concepts to university-level courses led by esteemed AI professionals. These materials provide a profound understanding of critical concepts in the fields of ML and AI, with a focus on advanced deep learning techniques.

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  • GraphCast (opens in a new tab): DeepMind introduces GraphCast, an AI model delivering unparalleled 10-day weather predictions in under a minute. Utilizing Graph Neural Networks and trained on extensive historical and current weather data, it outperforms the High Resolution Forecast system, forecasting cyclone paths, identifying atmospheric rivers, and enabling earlier warnings. (code) (paper in Science) (View GraphCast live on ECMWF) (paper)

  • GNoME (opens in a new tab) (Graph Networks for Materials Exploration), developed by DeepMind, predicts structures for over 2 million new materials, including 2.2 million crystals—equivalent to almost 800 years of knowledge. This breakthrough in materials science highlights 380,000 stable materials with potential applications in technologies like improved batteries, solar panels, and computer chips. (paper) (dataset)


  • The Little Book of Deep Learning (opens in a new tab) by François Fleuret, simplifies complex aspects of deep learning, such as machine learning, efficient computation, and training, including linear algebra, calculus, probabilities, optimization, signal processing, algorithmic, and high-performance computing.

  • Deep Learning (opens in a new tab) by Ian Goodfellow, a comprehensive guide that explores the depths of ML. Written by a renowned expert, practical examples, and an in-depth exploration of the mathematics behind deep learning. Immerse yourself in the world of ML, uncover its real-world applications, and pave the way for a dynamic career in this evolving field.

  • Deep Learning with Python (opens in a new tab) by François Chollet, designed for practicality, offering hands-on experiences with essential ML principles, accompanied by practical coding examples and proficiency. Dive into the realm of deep learning, apply it to real-world scenarios, and harness the potential of this dynamic field through coding.

  • Dive into Deep Learning (opens in a new tab) is an interactive, comprehensive guide to machine learning, particularly deep learning. It covers math, code, and real data experiments. The book is designed for accessibility, teaching concepts, context, and code. It introduces new concepts through self-contained examples using real datasets and notebooks, both theoretical and practical.