MLfromScratch

implementing machine learning algorithms without libs

Environments

singularity image, including

• jupyter lab, monokai+, kite
• statsmodels
• sklearn
• other basic packages, eg. numpy, matplotlib, pandas, math

Implemented Algorithms

Linear Algorithms

• Linear Regression
• Autoregression, AR
• Vector Autoregression with Exogenous variables, VARX
• Linear Discriminant Analysis, LDA

Nonlinear Algorithms

• Classification and Regression Tree, CART
• Naive Bayse, NB
• K-Nearest Neighbors, kNN
• Learning Vector Quantization, LVQ
• Support Vector Machine, SVM

Ensemble Algorthms

• Random Forest (bagging decision trees), RF
• AdaBoost

Neural Networks

References

• Master Machine Learning Algorithms, Jason Brownlee
• MIT 6.S191: Introduction to Deep Learning