Collection of machine learning algorithms written from scratch with numpy & pandas. Most code here is written to understand how they work. It is not optimized for production. Use it at your own risk.
Prerequisites:
- Python >= 3.x
- Graphviz >= 2.40 (on Ubuntu:
sudo apt install graphviz)
Setup steps:
- Clone this repo
- Install dependencies
pip install -r requirements.txt
- Decision Tree
- Naive Bayes Classifier
- Bayesian Network with Expectation-Maximization
- Join-Distribution Bayes Classifier
- Linear Regression vs Normal Equation
- Logistic Regression
- Hidden Markov Model
- Artificial Neural Network
The MIT License
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.