#other #artificial_intelligence #data_mining #data_science #deep_learning #game_theory #hardware #learning_theory #literature #machine_learning #machine_learning_algorithms #neural_network #paper #pattern_recognition #reinforcement_learning #silicon #statistical_learning #statistics

https://github.com/tirthajyoti/Papers-Literature-ML-DL-RL-AI

#jupyter_notebook #datascience #machine_learning #python #statistical_learning

https://github.com/hardikkamboj/An-Introduction-to-Statistical-Learning

#python #code #machine_learning_algorithms #statistical_learning_method

This resource helps you learn machine learning and AI by providing translated papers, detailed code explanations, and practical implementations. You can read hundreds of papers daily with translations of titles, summaries, and even full texts for some AI papers. The code is well-commented, making it easy to follow along with formulas and examples. There are also blogs and upcoming books to help you understand the concepts better. Additionally, there are plans for offline training sessions in major cities, which can help you quickly get started with ML, MLP, and CV. This makes learning machine learning more accessible and comprehensive.

https://github.com/Dod-o/Statistical-Learning-Method_Code

#other #ai #artificial_intelligence #deep_learning #intelligent_machines #intelligent_systems #machine_intelligence #machine_learning #neural_network #reinforcement_learning #statistical_learning #unsupervised_learning

This is a curated AI roadmap with books, courses, papers, tools, and agents for learning and building modern AI systems. It helps you quickly find trusted resources for RAG, agents, evals, deployment, and coding tools, so you can learn faster and build better AI products with less guesswork.

https://github.com/owainlewis/awesome-artificial-intelligence