Topics are categorized into introductory, intermediate, advanced and mixed levels.

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Deepmind shared a curated one perform of resources for people interested in artificial intelligence, machine learning, and related topics.

Topics are categorized into introductory, intermediate, advanced and mixed levels. The list includes links to newsletters, blog posts, videos, research papers, and online notes with information on artificial intelligence and machine learning topics. It also provides links to the best courses on AI and ML on Coursera, Colab notebooks, digital books, and podcasts to keep you up to date with the latest developments in neuroscience, deep learning, and robotics.

Some notable mentions from the list are:

1.A 2020 Vision of Linear Algebra (Gilbert Strang, MIT) summarizes an entire linear algebra course with technical details through a new lens: how linear algebra is applied to the real world, particularly in machine learning.

2. An overview of gradient descent optimization algorithms comprehensive blog post examining the main variants of gradient descent to optimize neural networks.

3. Brain inspired podcast where neuroscience and AI converge.

Deepmind has been at the forefront of research in the AI ​​space since 2010. The Deepmind research team aims to build new types of computers that can learn to find solutions to difficult problems on their own.
Access the list here.

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