vionwinnie/datascience-resources

keep track of data science resources that I like

Winnie's list of data science resources

• keep track of data science resources that I like and consult frequently

Data Science Learning Path

• Interactive Learning Path for basics, ML, data engineer, deep learning, https://github.com/AMAI-GmbH/AI-Expert-Roadmap

Data Manipulation

• Kevin Markham's Pandas and Scikit-learn tips: https://github.com/justmarkham
• Jose Portilla Course on Udemy and the github: https://github.com/jmportilla/Complete-Python-Bootcamp

Regression

• Prediction Intervals: https://online.stat.psu.edu/stat501/lesson/3/3.3

Machine Learning Basics

• Linear Algebra Geometric Interpretation: https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
• Georgia Tech ISYE6501 by Joel Sokol
• AB Testing:

Cheatsheets

• Probability: https://github.com/wzchen/probability_cheatsheet
• Pandas: https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf
• Numpy:https://s3.amazonaws.com/dq-blog-files/numpy-cheat-sheet.pdf

Model Interpretability

• Book: https://christophm.github.io/interpretable-ml-book/
• On LIME: https://homes.cs.washington.edu/~marcotcr/blog/lime/

Natural Language Processing

• Juraksky's material on NLP: https://web.stanford.edu/~jurafsky/slp3/
• NLP 2012 Dan Jurafsky and Chris Manning Lectures: https://www.youtube.com/playlist?list=PLoROMvodv4rOFZnDyrlW3-nI7tMLtmiJZ
• ISYE 7650: https://www.cc.gatech.edu/classes/AY2020/cs7650_spring/
• Coursera NLP Specialization: https://www.coursera.org/specializations/natural-language-processing#courses

Big Data Mining

• Mining Massive Dataset: http://www.mmds.org/

Advanced Machine Learning / Bayesian

• https://deepbayes.ru/2019/
• https://smiles.skoltech.ru/school

Spark / Distributed Computing

• Excellent videos for overall architecture: https://www.youtube.com/watch?v=AsIx95xHOIM&list=PLkz1SCf5iB4dXiPdFD4hXwheRGRwhmd6K
• PySpark: https://realpython.com/pyspark-intro/
• Twitter primer on Scala: https://twitter.github.io/scala_school/

MLOps

• Docker, Kubernetes, Flask: https://www.youtube.com/playlist?list=PL3N9eeOlCrP5PlN1jwOB3jVZE6nYTVswk
• Python for Devops (Book)

Machine Learning System Design

• https://github.com/chiphuyen/machine-learning-systems-design
• Stanford MLSys Seminar: https://www.youtube.com/channel/UCzz6ructab1U44QPI3HpZEQ

Machine Learning Interviews Prep

• I follow several people on LinkedIn who post interesting content:

1. Dan Lee: https://www.linkedin.com/in/danleedata/
2. Eric Webter on SQL: https://www.linkedin.com/in/eric-weber-060397b7/