Machine Learning Cheat Sheet
These Notebooks Contain:
- Explaining Various machine learning algorithms concepts and implementing them using libraries like scikit learn.
- Implementing various machine learning algorithms from scratch:
- Logistic Regression
- KNN
- Decision Tree
- Gaussian Mixture Models
- LDA
- QDA
- Naive Bayes
- PCA
- How to use Pandas and Scikit Learn libraries for data wrangling and preprocessing.
- How to perform hyperparameter tuning using various methods and packages.
- Explanation for Feature Engineering, Feature Selection, and Feature Extraction and how to implement some of these methods.
NOTE: there is no deep learning here.
NOTE: still ongoing project (last update: August 2022)