This repository is to demonstrate Neural Networks and Support Vector Machine based regression methods.

This classifier achieved the following results, "Percent humans misclassified as dogs is 1%. and "Percent of dogs correctly classified is 100%" It is very reliable when it comes to classification of dog breeds.

Restaurant Revenue Prediction - Kaggle Competition

Forest type predictor trained on NDVI data using a feed forward Neural Network

Machine Learning model to predict the scores of NFL games

Using time series model to estimate the remanning parking space to guide the people who is waiting for parking space

Multiresponse time-to-event Cox proportional hazards model - GPU

Uber Traveling Time Analytics in DC Census Tract Zones

Age recognition by single photo

Regression Analysis with the BikeShare data.

✈️ Flight delay EDA & estimation on a 12GB dataset using a custom C++ OLS estimator.

Heart disease prediction

API for data prediction 📈

Understanding and predicting the factors leading to employees leaving and finding relations between them. Also finding the importance of a feature according to ML models.

COVID19 eda and forecast/prediction model

Analyzed, Cleaned and Visualised dataset of different patients. Built a ML-Model using Python and Machine Learning that predicts whether a person is diabetic or not

This project creates a web application which predicts fashion items uploaded as image using a parallelized machine learning model trained on the Fashion-MNIST dataset and also analyzes the performance of different parallelized classifier models.