In this repository, I'll be documenting the content related machine learning and deep learning trainings and related resources.
I required this space to document these stuff.
- Deep Learning Course 14x050 of the University of Geneva - François Fleuret - https://fleuret.org/dlc/
- DS-GA 1008 · SPRING 2020 - Yann LeCun & Alfredo Canziani - https://atcold.github.io/pytorch-Deep-Learning/
- mlcourse.ai · OpenDataScience - Yury Kashnitsky - https://mlcourse.ai/
- MIT 6.S191 Introduction to Deep Learning - Alexander Amini & Ava Soleimany - http://introtodeeplearning.com/
- Deep Learning and Artificial Intelligence Lectures · MIT - Lex Fridman, Research Scientist - https://deeplearning.mit.edu/
- TensorFlow 2.0 Complete Course - Python Neural Networks for Beginners Tutorial - freeCodeCamp.org - https://www.youtube.com/watch?v=tPYj3fFJGjk
- Neural Networks for Machine Learning - Geoffrey Hinton - https://www.youtube.com/playlist?list=PLoRl3Ht4JOcdU872GhiYWf6jwrk_SNhz9
- Deep Learning in Computer Vision - Prof. Kosta Derpanis - https://www.eecs.yorku.ca/~kosta/Courses/EECS6322/
- Deep Learning Course of Unige/EPFL - François Fleuret/University of Geneva - https://fleuret.org/dlc/
- CS109a: Introduction to Data Science - Pavlos Protopapas, Kevin A. Rader, and Chris Tanner - https://harvard-iacs.github.io/2019-CS109A/
- ML Course Notes - Democratizing Artificial Intelligence Research - https://github.com/dair-ai/ML-Course-Notes
- Advance Computer Vision Course - Mubarak Shah - https://www.crcv.ucf.edu/courses/cap6412-spring-2022/schedule/
- Introduction to Deep Learning (I2DL) (IN2346) - Prof. Matthias Nießner - https://niessner.github.io/I2DL/
- CS 25: Transformers United - Div Grag, et. al. - https://web.stanford.edu/class/cs25/
- ECS498-007: Deep Learning for Computer Vision - Justin Johnson - https://web.eecs.umich.edu/~justincj/teaching/eecs498/FA2019/schedule.html
- Introduction to Machine Learning - Google - https://developers.google.com/machine-learning/crash-course/ml-intro
- UvA Deep Learning Tutorials - Phillip Lippe - https://uvadlc-notebooks.readthedocs.io/en/latest/index.html, https://www.youtube.com/playlist?list=PLdlPlO1QhMiAkedeu0aJixfkknLRxk1nA
- Applied Machine Learning (Cornell CS5785) - Volodymyr Kuleshov - https://www.youtube.com/playlist?list=PL2UML_KCiC0UlY7iCQDSiGDMovaupqc83
- Carnegie Mellon University Deep Learning - 11785 Fall 2022 - Bhiksha Raj and Rita Singh - https://www.youtube.com/playlist?list=PLp-0K3kfddPxRmjgjm0P1WT6H-gTqE8j9
- Machine Learning Blinks - BASIRA Lab- https://www.youtube.com/playlist?list=PLug43ldmRSo1LDlvQOPzgoJ6wKnfmzimQ
- CS5785 Applied Machine Learning at Cornell University and Cornell Tech - Volodymyr Kuleshov, Nathan Kallus, Serge Belongie - https://kuleshov-group.github.io/aml-book/intro.html
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Deep Learning · Ian Goodfellow and Yoshua Bengio and Aaron Courville - https://www.deeplearningbook.org/
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Data Science and Machine Learning: Mathematical and Statistical Methods · D.P. Kroese, Z.I. Botev, T. Taimre, R. Vaisman - https://acems.org.au/data-science-machine-learning-book-available-download
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The Machine & Deep Learning Compendium - https://mlcompendium.gitbook.io/machine-and-deep-learning-compendium/
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Interpretable Machine Learning - A Guide for Making Black Box Models Explainable - https://christophm.github.io/interpretable-ml-book/
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Introduction to Probability for Data Science - Stanley H. Chan - https://probability4datascience.com/
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Neural Networks and Deep Learning - Michael Nielsen - http://neuralnetworksanddeeplearning.com/
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Dive into Deep Learning - Ston Zhang, Zachary C. Lipton, Mu Li, And Alexander J. Smola - http://d2l.ai/
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Understanding Deep Learning - Simon J.D. Prince - https://udlbook.github.io/udlbook/
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Algorithms for Decision Making - Mykel J. Kochenderfer, Tim A. Wheeler, and Kyle H. Wray - https://algorithmsbook.com/
- Machine Learning Tutorials from ujjwalkarn - https://github.com/ujjwalkarn/Machine-Learning-Tutorials
- List of Aman Chadha - https://aman.ai/
- applied-ml by eugeneyan - https://github.com/eugeneyan/applied-ml#recommendation
- AI Curriculum - Machine Learning Tokyo - https://github.com/Machine-Learning-Tokyo/AI_Curriculum
- List of Sam Finlayson - https://sgfin.github.io/learning-resources/?s=08#misc