Machine learning algorithm implementations and explanations
The notebooks contains derivations and explanations of each method followed by implementations and example usage on well know data sets
This contains the source code for each of the implementations (these are the same as in each notebook)
- Linear regression
- Logistic regression
- Knn
- Decision tree
- Random forest
- Gradient boosted decision tree
- Neural network