gauravchopracg/linear-models

try to separate objects with a plane which divides space into two parts

TODO:

1. Basic ML models

• Linear
• Tree-based
• K-NN
• Neural Network

2. EDA-1

• Basic feature types.
• preprocess them with respect to models

3. Validation Strategies
4. Data Leakage, Leaderboard probing
5. Metrics: Classification, regression and their optimization
6. EDA-2

• mean encoding of time series, categorical data

7. Advanced feature generation
8. Hyperparameter optimization

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Books: http://www2.ift.ulaval.ca/~chaib/IFT-4102-7025/public_html/Fichiers/Machine_Learning_in_Action.pdf http://www.deeplearningbook.org/