classical ML & statistics: 8 curated resources
classical ML & statistics
8 resources · page 1 of 1
MindSpore framework
by MindSpore
MindSpore GitHub repo: Huawei's open-source deep learning training and inference framework.
3Blue1Brown Neural Networks
by Grant Sanderson (3Blue1Brown)
3Blue1Brown neural networks series: visual video lessons explaining neural networks, backpropagation and transformers.
An Introduction to Statistical Learning
by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani
Author site for An Introduction to Statistical Learning, with free PDF and labs in R and Python.
Deep Learning School (DLS) МФТИ
by Deep Learning School (MIPT)
Deep Learning School from MIPT: free Russian-language online course on computer vision, NLP, LLMs and generative models.
fast.ai Practical Deep Learning
fast.ai Practical Deep Learning for Coders: free course teaching deep learning through code-first notebooks.
Neural Networks: Zero to Hero (Karpathy)
Andrej Karpathy's Neural Networks: Zero to Hero video course, building micrograd, makemore, GPT and a tokenizer in code.
Full Stack Deep Learning
Full Stack Deep Learning site with course materials and LLM Bootcamp lectures on building AI-powered products.
YSDA Practical Deep Learning
by Yandex School of Data Analysis
YSDA Practical_DL GitHub repo: deep learning course materials from Yandex School of Data Analysis, HSE and Skoltech.