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An open-source knowledge-sharing project . |
The following is my personal compendium, which includes many topics, such as links, summaries in the fields of statistics, machine learning, deep learning, computer science, data science, deep vision, NLP, cloud computing, product management, and others.
I see this compendium as a gateway, as a frequently visited resource for people of proficiency levels, for industry data scientists, and academics. It includes various summaries, links, and articles that I have read on every topic that I found interesting, or that I had needed to learn, which include the majority of modern machine learning algorithms, feature selection and engineering techniques, deep-learning, NLP, audio, vision, time-series, anomaly detection, experiment management, and much more. In addition to strategic topics such as data science management and team building,
The compendium will save you countless hours googling and sifting through articles that may not give you any value.
I believe in knowledge sharing and the compendium will always be free to everyone. Previously the Compendium was in a 407-page google doc, but It has gone fully open-source and is now hosted on Gitbook & Github (please star it).
Please keep in mind that this is a perpetual work in progress with a variety of topics. If you feel that something should be changed, please use the comment option and let me know.
I would like to thank the following contributors: Samuel Jefroykin, Sefi Keller
Many Thanks,
Dr. Ori Cohen | LinkedIn| Medium | OriCohen.com | MLCompendium.com | book.mlcompendium.com