Further reading
The following are a few resources that you can explore for a detailed study:
- Learning From Data by Yaser Abu-Mostafa: https://work.caltech.edu/lectures.html.
- Curse of Dimensionality – Georgia Tech: https://www.youtube.com/watch?v=OyPcbeiwps8.
- Dummy Variable Trap: https://www.learndatasci.com/glossary/dummy-variable-trap/.
- Using deep learning to learn categorical embeddings: https://pytorch-tabular.readthedocs.io/en/latest/tutorials/03-Extracting%20and%20Using%20Learned%20Embeddings/.
- Handling categorical features – CatBoost: https://catboost.ai/en/docs/concepts/algorithm-main-stages_cat-to-numberic.
- Exploring Bayesian Optimization – from Distil.pub: https://distill.pub/2020/bayesian-optimization/.
- Frazier, P.I. (2018). A Tutorial on Bayesian Optimization. arXiv:1807.02811 [stat.ML]: https://arxiv.org/abs/1807.02811.
- Time series clustering using
tslearn: https://tslearn.readthedocs.io/en/stable/user_guide/clustering...
