# Linear Algebra
[Khan Academy Linear Algebra series (beginner friendly).](https://www.khanacademy.org/math/linear-algebra)
[Coding the Matrix course (and book).](http://codingthematrix.com/)
[3Blue1Brown Linear Algebra series.](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab&fbclid=IwAR0aMT4mHp-BAy5viaJyggcQqgBCTbP0VVm3ZaiGTDeyGKHn7cK_Hi-LpFA)
[fast.ai Linear Algebra for coders course, highly related to modern ML workflow.](https://github.com/fastai/numerical-linear-algebra/blob/master/README.md)
[First course in Coursera Mathematics for Machine Learning specialization.](https://www.coursera.org/specializations/mathematics-machine-learning)
[“Introduction to Applied Linear Algebra — Vectors, Matrices, and Least Squares” book.](https://web.stanford.edu/~boyd/vmls/) [MIT Linear Algebra course, highly comprehensive.](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/index.htm)
[Stanford CS229 Linear Algebra review.](http://cs229.stanford.edu/section/cs229-linalg.pdf)
[The Matrix Cookbook](http://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf)
[Basic Linear Algebra for Deep Learning](https://towardsdatascience.com/linear-algebra-for-deep-learning-f21d7e7d7f23)
Khan Academy Calculus series (beginner friendly).
3Blue1Brown Calculus series.
Second course in Coursera Mathematics for Machine Learning specialization.
The Matrix Calculus You Need For Deep Learning paper.
MIT Single Variable Calculus.
MIT Multivariable Calculus.
Stanford CS224n Differential Calculus review.
Khan Academy Statistics and probability series (beginner friendly).
A visual introduction to probability and statistics, Seeing Theory.
Intro to Descriptive Statistics from Udacity.
Intro to Inferential Statistics from Udacity.
Statistics with R Specialization from Coursera.
Stanford CS229 Probability Theory review.
Think Stats 2e
[Part one of Deep Learning book.](http://www.deeplearningbook.org/)
[CMU Math Background for ML course.](https://www.youtube.com/playlist?list=PL7y-1rk2cCsA339crwXMWUaBRuLBvPBCg)
[The Math of Intelligence playlist by Siraj Raval.](https://www.youtube.com/playlist?list=PL2-dafEMk2A7mu0bSksCGMJEmeddU_H4D)
[Data Science from Scratch, 2nd Edition](https://www.oreilly.com/library/view/data-science-from/9781492041122/)
[Introduction to Machine Learning with Python](https://www.oreilly.com/library/view/introduction-to-machine/9781449369880/)
[Pragmatic AI: An Introduction to Cloud-Based Machine Learning, First Edition](https://www.oreilly.com/library/view/pragmatic-ai-an/9780134863924/)
[Python Machine Learning](https://www.oreilly.com/library/view/python-machine-learning/9781119545637/)
[Path to a free self-taught education in Data Science!](https://github.com/ossu/data-science)
[Data-Science--Cheat-Sheet](https://github.com/abhat222/Data-Science--Cheat-Sheet)
[stanford-tensorflow-tutorials](https://github.com/chiphuyen/stanford-tensorflow-tutorials)
[datasciencecoursera](https://github.com/mGalarnyk/datasciencecoursera)
[AmpliGraph](https://github.com/Accenture/AmpliGraph)
[awesome-knowledge-graph](https://github.com/totogo/awesome-knowledge-graph)
[kglib](https://github.com/graknlabs/kglib)
[awesome-knowledge-graph](https://github.com/shaoxiongji/awesome-knowledge-graph)
[Knowledge-Graph-Analysis-Programming-Exercises](https://github.com/SmartDataAnalytics/Knowledge-Graph-Analysis-Programming-Exercises)
[knowlegegraph-demo](https://github.com/arangoml/knowlegegraph-demo)
[OpenKE](https://github.com/thunlp/OpenKE)
[linguist-python](https://github.com/scivision/linguist-python)
[linguist](https://github.com/douban/linguist)
[django-linguist](https://github.com/ulule/django-linguist)
[nlp-python-deep-learning](https://github.com/NirantK/nlp-python-deep-learning)
[NLP-with-Python](https://github.com/susanli2016/NLP-with-Python)
[Hands-On-Natural-Language-Processing-with-Python](https://github.com/PacktPublishing/Hands-On-Natural-Language-Processing-with-Python)
[nlp-in-python-tutorial](https://github.com/adashofdata/nlp-in-python-tutorial)
[text-classification](https://github.com/javedsha/text-classification)
[20newsgroups-text-classification](https://github.com/yanqiangmiffy/20newsgroups-text-classification)
[Hidden-Markov-Model-for-NLP](https://github.com/FantacherJOY/Hidden-Markov-Model-for-NLP)
[text-kmeans-clustering-with-python](https://github.com/MNoorFawi/text-kmeans-clustering-with-python)
[Text-Clustering](https://github.com/Ruchi2507/Text-Clustering)
[Text-classification-and-clustering](https://github.com/abhijeet3922/Text-classification-and-clustering)
[Text-Clustering](https://github.com/sowmyagowri/Text-Clustering)
[Text-Clustering](https://github.com/AymanKh/Text-Clustering)
K-means-Clustering-on-Text-Documents
https://github.com/ahawker/data-analysis-coursera
https://github.com/secure-data-analysis-data-sharing/data-analysis
https://github.com/googleanalytics/google-analytics-super-proxy
https://github.com/triestpa/Cryptocurrency-Analysis-Python
https://github.com/fenglei110/Data-analysis
https://github.com/zhichaoluo/DataAnalysis
https://github.com/arunma/ScalaDataAnalysisCookbook
https://github.com/TheisTrue/DataAnalysis
https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook
https://github.com/realXuJiang/course
https://github.com/mike-works/sql-fundamentals
https://github.com/exlskills/course-sql-introduction/tree/master/00_SQL
https://github.com/ayushi-b/SQL-for-Data-Analysis
https://github.com/caveofprogramming/mysql-course
https://github.com/SLPeoples/MySQL-for-Data-Analytics-and-Business-Intelligence
https://github.com/yanfei-wu/MySQL-Coursera-Duke
https://github.com/SoftwareIntrospectre/The-Complete-SQL-Bootcamp
https://github.com/michaelbironneau/analyst
https://github.com/shankhapaul22/Business-Data-Analysis-with-SQL
https://github.com/Albertsr/Data-Analysis
https://github.com/FantasyFootballAnalytics/FantasyFootballAnalyticsR
https://github.com/susanli2016/Data-Analysis-with-R
https://github.com/stefmolin/Hands-On-Data-Analysis-with-Pandas
https://github.com/founderfan/Data-Open-Analysis
https://github.com/Azure/LearnAnalytics-mr4ds
https://github.com/TrainingByPackt/Data-Science-for-Marketing-Analytics
https://github.com/anabranch/data_analysis_with_python_and_pandas
https://github.com/apachecn/python_data_analysis_and_mining_action
https://github.com/yenlung/Python-3-Data-Analysis-Basics
https://github.com/fonnesbeck/statistical-analysis-python-tutorial
https://github.com/cuttlefishh/python-for-data-analysis
https://github.com/Tatvic/RGoogleAnalytics
https://github.com/pilsung-kang/text-analytics
https://github.com/justmarkham/python-data-analysis-workshop
https://github.com/DataScienceSpecialization/Exploratory_Data_Analysis
https://github.com/PacktPublishing/Mastering-Python-Data-Analysis
https://github.com/zjdian/data-analysis
https://github.com/MicrosoftLearning/Essential-Math-for-Data-Analysis
https://github.com/Echo9573/DataAnalysisbyPython
https://github.com/MicrosoftLearning/Introduction-to-Data-Analysis-using-Excel
https://github.com/amangup/data-analysis-bootcamp
https://github.com/microsoft/Resource-Static-Analysis
https://github.com/AbdullahAlrhmoun/Data-analysis-learning-projects
https://github.com/WillKoehrsen/Data-Analysis
https://github.com/rhiever/Data-Analysis-and-Machine-Learning-Projects
https://github.com/aloctavodia/Doing_bayesian_data_analysis
https://github.com/udacity/data-analyst
https://github.com/yenlung/Python-3-Data-Analysis-Basics