harrisonll / machine_learning

Notebooks for ML theories, Deep Learning, data preprocessing techniques. Keep updating.

Machine_Learning (keep updating)

This repo includes notes of traditional machine learning models (math, pros & cons), data preprocessing techniques, and deep learning models. Notes are mainly summarized from EECS 545 (Machine Learning) and STATS 503 (Statistical Learning) at the University of Michigan. It also includes studies out of school.

1. The "ML-Data-Analysis.txt" file is a short summary of tranditional ML models and data analysis techniques.
2. The "Machine Learning Notes .pdf" includes tranditional ML algorithm in details.
3. The "NLP_basics_summary.txt" is a summary of NLP data preprocessing techniques.
4. The "Deep Learning and NLP.pdf" includes deep learning techniques such as LSTM, transformers, and BERT. It also includes some models that I researched and built during summer internship in 2021.