This project applies machine learning techniques (multiple classification) to predict the severity of traffic accidents using historical data.

This library gives a modular design for better control of gradient passing between architecture components. Useful for architectures not using a traditional forward and backward pass.

Different machine learning approaches on classifying customers who are most likely to purchase an offer. Made with Jupyter Notebook, scikit-learn, and other helpful python packages.

A machine learning project that performs sentiment analysis on Twitter data using Logistic Regression in Python. The model classifies tweets as Positive, Negative, or Neutral based on their text content.

Using R programming language to create a logistic regression model so we can predict whether someone have diabetes or not based on health marker