Building a model to predict demand of shared bikes. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels.

Training a model to predict whether a given job posting is fake or not

Binary classification and Multiclass classification with pipelining and parameter tuning with GridsearchCV and RandomizedSearchCV

A library of codeblocks for common algorthims,patterns,and utilities that can be easily integrated into any project.

This project aims to analyze and predict house prices based on various features such as location, size, and amenities. The dataset is processed and explored using Python, and machine learning models are applied to generate accurate price predictions.

The tasks I was required to complete as a part of the BCG Open-Access Data Science & Advanced Analytics Virtual Experience Program are all contained in this repository. This virtual internship was sponsored by Forage📊📈📉👨‍💻

Welcome to the Loan Approval Prediction project repository! This project focuses on predicting the approval of loan applications using various machine learning algorithms. By analysing applicant details and financial information, the model aims to assist financial institutions in making data-driven and reliable loan approval decisions.

Titanic Machine Learning from Disaster

This is a machine learning model built in python3 to predict transaction conversion of web visits for an e-commerce website.

This repository serves as a comprehensive resource for understanding and implementing various feature selection techniques, gaining familiarity with Jupyter Notebook, and mastering the process of model training and evaluation

A web application that employs machine learning models to provide accurate and instant car price estimations based on various features and specifications.

This is the second project I completed as part of the Machine Learning Module from my post-graduate certification in AI/ Machine Learning from University of Texas' McCombs School of Business.

This Project is about to identify if a person's back pain is abnormal or normal using collected physical spine details/data.

The aim of this project is to predict fraudulent credit card transactions using machine learning models.

This repo hosts an end-to-end machine learning project designed to cover the full lifecycle of a data science initiative. The project encompasses a comprehensive approach including data Ingestion, preprocessing, exploratory data analysis (EDA), feature engineering, model training and evaluation, hyperparameter tuning, and cloud deployment.

This project aims to develop a machine learning model for proactive fraud detection in financial transactions.

his project demonstrates a machine learning approach to predicting loan approvals based on applicant data. Built with Python, the model leverages the Random Forest Classifier for robust predictive performance. This project is ideal for those interested in data preprocessing, feature engineering, and classification in financial datasets.

Build and Deploy a binary classification model as a plagiarism detector

The given data includes airline reviews from 2016 to 2019 for popular airlines around the world with multiple choice and free text questions. Data is scrapped in spring2019.The main objective is to predict whether passengers will refer the airline to their friends.