Essential Python libraries for Machine Learning regression
and classification problems:
- Shallow
learning: XGBoost
(gradient boosting).
- Deep learning, perceptive
problems: Keras as
TensorFlow front end.
- Feature preprocessing and model selection pipelines:
Scikit-Learn.
Both XGBoost and Keras have wrappers for the Scikit-Learn
API. Scikit-Learn is also useful to try regression and
classification models of incremental difficulty, and for
clustering and data reduction problems.
All the above libraries have good documentation and extensive
examples that can be integrated with the following references: