ML-with-Python [WIP]

In this repository, I create simple projects from classical machine learning, e.g.:

• Classification
  • Logistic Regression
  • k-NN Regression
  • Decision Trees
  • Random Forests
  • Gradient Boosting
  • Projected Random Forest
• Clustering
  • Autoencoders
  • Variational Autoencoders

Install

Prerequisite: python >= 3.6

1. Install venv

venv_name=venv
python -m venv $venv_name  # install venv
source $venv_name/bin/activate  # activate venv

2. Install requirements

pip install --upgrade pip  # update pip
pip install -r requirements.txt  # install required packages

Structure

.
├── data
│   ├── diabetes
│   └── mnist
├── notebooks
│   ├── Decision Trees.ipynb
│   ├── Gradient Boosting.ipynb
│   ├── KNN Regression.ipynb
│   ├── Logistig Regression.ipynb
│   ├── Projected Random Forest.ipynb
│   └── Random Forest.ipynb
├── results
│   ├── models
│   └── outputs
├── src
│   ├── helper
│   │   ├── __init__.py
│   │   ├── helper_clean_diabetes.py
│   │   ├── helper_mnist_download.py
│   │   ├── helper_sklearn_plotting.py
│   │   └── wrapper_random_projection.py
│   └── __init__.py
├── README.md
└── requirements.txt

Created with tree

tree --dirsfirst -I "$(grep -hvE '^$|^#' {~/,,$(git rev-parse --show-toplevel)/}.gitignore|sed 's:/$::'|tr \\n '\|')"