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.

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.

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.

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