This project focuses on developing a deep learning-based solution for predicting the probability of the end of the visible road in street camera videos using corresponding road segmentation images. The chosen approach is a modified UNet architecture with a 1-dimensional decoder. The resulting model efficiently and accurately analyzes and extracts spatially meaningful vectors, such as the likelihood of a road ending, from street camera videos for various traffic management and autonomous vehicle applications.

Google Colab notebook 

In this Exploratory Data Analysis project, we used various machine learning models on the Wisconsin Breast Cancer dataset to predict malignant tumors. We employed feature analysis and PCA to deal with high dimensionality, and stratified cross-validation to handle class imbalance. 

Google Colab notebook

This project visually explores global temperature data, showcasing distinct land-ocean and continent-based temperature trends through interactive Python Plotly plots. It offers a snapshot of climate change, demonstrating temperature progression over time across diverse geographical regions. 

Google Colab notebook

The Forecasting Super Store Sales project provides a simple, yet comprehensive, insight into commercial sales through time series analysis. This project encompasses everything from importing necessary libraries to data exploration, anomaly detection, and future sales forecasting.

Google Colab notebook