The nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures

Successfully developed a machine learning model which can accurately predict the strength of cement based on various features such as blast furnace slag, water, coarse aggregate, etc.

Successfully established a machine learning model to accurately predict the price of a flight in India based on several features such as duration, days left, arrival time, departure time and so on.

Successfully developed a machine learning model which can accurately predict up to 100% accuracy whether a credit card application of a given applicant would be approved or not, based on several demographic features such as applicant age, total income, marital status, total years of work experience, etc.

Comment classifier model trainer using keras tensorflow, stanza tokenizer and transformers.

The enhancement of Intelligent Transport Systems (ITS) involves the precise prediction of bike-trip durations, incorporating a comprehensive consideration of Seoul's weather conditions.

Simple ML system for the iris problem

University Admission Predictor is a sophisticated Flask-based web application designed to predict the likelihood of admission to graduate programs based on student profiles. It leverages a range of regression techniques to evaluate admission chances.This project showcases the practical application of machine learning in educational forecasting.

This repository contains a machine learning project aimed at predicting housing prices in Boston. This project showcases the end-to-end process of building and deploying a machine learning model, from data preprocessing and model training to serialization and deployment.

Zomato delivery time prediction

Successfully established a machine learning model which can accurately predict the expected life duration of a human being based on several demographic features such as alcohol consumption per capita, average BMI of entire population, etc.

Successfully developed a machine learning model which can accurately classify the weather based on various features pertaining to weather-related data and atmospheric conditions.

Successfully created a machine learning model which can accurately predict the fare of a taxi trip based on several features such as trip duration, tip amount, etc.

Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.

Nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures. Using machine learning and neural networks, you’ll use the features in the provided dataset to create a binary classifier that can predict whether applicants will be successful if funded.

Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.

Deployment ready machine learning model to predict the math scores of students based on various features related to their demographics, background, and academic engagement.

This repository contains several ML algorithms wriiten from scratch that are covered in ML lab.

Code that can be used for training a neural network model to detect faults (sticky notes, folded corners etc.) in input documents.

Code that can be used for training a neural network model to classify input documents into distinct classes.