Deep Learning Resources

Books

• FastBook
• Python Data Science Handbook - By Jake VanderPlas
• Python for Data Analysis - By Wes McKinney | Book to learn about data handling with standard ML Libraries

Guides

• https://www.interviewbit.com/system-design-interview-questions/amp/
• https://www.promptingguide.ai/ Prompt Engineering
• https://medium.com/marvelous-mlops/mlops-roadmap-2024-ff4216b8bc62 Mooc
• The Missing Semester of Your CS Education (mit.edu) MIT Missing CS Semester + Lectures: Teaches how to use system utility tools like git, vim, other useful untaught methods for Machine Learning.
• https://hepsoftwarefoundation.org/training/center.html Multiple Advance Tutorial/Guide Series. Recommended

Lectures

• Cornell Machine Learning for Intelligent Systems 2018 36 Lectures and different Assignments https://www.youtube.com/watch?v=MrLPzBxG95I&list=PLl8OlHZGYOQ7bkVbuRthEsaLr7bONzbXS

References

• Commands : List of Command Line Commands | Codecademy
• Bash vs Windows : Learn the Command Line | Codecademy
• Virtual Environment : Python: Modules | Codecademy
• Statistics Cheat Sheet : https://terenceshin.medium.com/week-2-52-stats-cheat-sheet-ae38a2e5cdc6
• Statistics in Maths: Definition, Types, Formulas, and Applications (geeksforgeeks.org)
• APIs : https://github.com/TwilioDevEd/introduction-to-apis-notes/blob/main/course-notes.md
• How web works : https://github.com/TwilioDevEd/introduction-to-apis-notes/blob/main/course-notes.md

Repositories

Good for Beginners

• Matlab + Python | Guided GitHub - radekosmulski/10_neural_nets
• https://www.instagram.com/p/C1W4QlzLBER/?igsh=MWFma29oM21qandnYg==
• https://diegoinacio.github.io/machine-learning-notebooks-page/

Tutorials/Videos

Papers