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.

sms spam ham classification using NLP Techniques

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

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.

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

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

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

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.

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.

Internship in Codeway Solution Company

Using publically available data for the national factors that impact supply and demand of homes in US, build a model to study the effect of these variables on home prices.

Model to identify the potential lead by assigning a score for their rate of conversion. Therefore, reaching out to potential is no more a brainstorming task.

In this project Utilizing advanced time series forecasting models, successfully predicted department-wide sales for each store for the upcoming year and Visualizing the data in streamlit GUI.

Semantic Similarity on SNLI dataset using BERT as well as TF-IDF+BERT(Pooled) embeddings.

The main purpose of this repository is to build the pipeline for training of regression models and predict the compressive strength of concrete to reduce the risk and cost involved in discarding the concrete structures when the concrete cube test fails.