Welcome to the Machine Learning Repository - Part 4! This repository focuses on unsupervised machine learning algorithms, particularly clustering techniques, and explores the fascinating world of ensemble methods, including boosting and bagging.

This project demonstrates the working of tensorflow-extended for creating scalable ML pipelines as well to automate CI/CD pipelines.

Exploratory Data Analysis & predicting medical insurance cost with machine learning.

sms spam ham classification using NLP Techniques

Car Price Prediction: Machine Learning (Data Science) Project using CarDekho.com dataset predicting prices of cars

A bike-sharing system is a service in which bikes are made available for shared use to individuals on a short term basis for a price or free. Many bike share systems allow people to borrow a bike from a "dock" which is usually computer-controlled wherein the user enters the payment information, and the system unlocks it.

Multi Linear Regression - Assignment - 50 Startups

To model the demand for shared bikes with the available independent variables

This Repo will contain the Machine Learning code and projects I will be doing

Student Exam Performance Indicator: ML Project Repository for analyzing and predicting student performance. Explore data, build models, and gain insights with ease.

A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies

An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.

The motive of this project is to find out the customer satisfaction of some residential hotels of Dhaka.

Internship in Codeway Solution Company

In our internship at Mentorness, we explored T20 World Cup data, using machine learning with expert guidance. Our team analyzed player performance and game outcomes, demonstrating the influence of mentorship on applying machine learning in cricket analytics.

A project to predict the average prices of Avocado in USA.

Designed an end-to-end ML model pipeline, forecasting department-wide sales by accounting for holiday markdown effects, spanning data collection to inferencing.

enhance real-time visual perception, offering intelligent support for tasks ranging from object recognition to detailed analysis and decision-making.

Building different machine learning models and selecting the best model for the given dataset. Saving the metrics ,parameters, artifacts, models in mlflow and using restapi for making predictions on validation data using the best model chosen.

The Global Superstore dataset is a comprehensive collection of sales data spanning multiple years, regions, and product categories. This rich dataset encapsulates critical business metrics including sales revenue, profit, order quantity, and shipping cost, making it ideal for various data analysis and machine learning projects.