Raga Classification Using Deep Learning This project focuses on Indian classical raga classification using deep learning. Unlike Western music genres, ragas are modal structures with intricate ornamentations and improvisations, requiring specialized feature extraction and model selection

This project tackles the Kaggle Titanic challenge. The objective is to build a predictive model to determine which passengers survived the Titanic disaster based on various features such as passenger class, age, gender, and other attributes. The project covers data cleaning, preprocessing, exploratory data analysis, and model building.

This project tackles the Kaggle Spaceship Titanic challenge. The solution includes comprehensive data preprocessing, feature engineering, exploratory data analysis (EDA), and modeling with LightGBM using stratified K-fold cross-validation.

This project aims to develop a machine learning model that predicts the prices of cars based on various factors such as make, model, year, mileage, engine size, and fuel type. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

A predictive analytics project leveraging machine learning algorithms to forecast the likelihood of heart disease in patients. Heart Disease Prediction Using Machine Learning Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

Email-Sms-Spam-Classifier

Scalable Machine Learning and Deep Learning, Final Project, 2023/2024

I developed a sophisticated ML model using LLMs to predict user preferences in chatbot interactions.implemented a comprehensive data preprocessing pipeline,including feature extraction and encoding,to optimize performance. conducted extensive hyperparameter tuning and evaluation, enhancing accuracy and in AI-driven conversational systems.

Classic Machine learning predictions + Feature Engi

Zomato Dataset: Restaurant & Food Exploratory Data Analysis (EDA) for data preprocessing and preparation for machine learning models.

Black Friday Dataset: E-commerce Exploratory Data Analysis (EDA) and Feature Engineering for data preprocessing and preparation for machine learning models.

This repository contains a comprehensive analysis of Beijing housing data, including data cleaning, categorical transformation, outlier removal, feature engineering, and advanced visualizations. The analysis focuses on understanding price trends, the impact of location, and district-level insights from 2010 onwards.

This repository contains a solution for Kaggle competition-Titanic-Machine Learning from Disaster

This project develops a machine learning model to predict customer churn for a California-based telecom company using data from 7043 customers. Our goal is to enhance customer retention strategies through detailed data analysis and feature engineering.

Developed a comprehensive data analysis project focusing on Walmart sales data. Imported raw sales data into a MySQL database and applied data transformation techniques to enrich and clean the dataset. Implemented various SQL queries to extract meaningful insights and generate actionable business recommendations.

this project develops a robust machine learning model to estimate house prices in the state.

Идентификация посетителя в зависимости от характерного времени его прохода на территорию организации

This project works on data of different laptop features according to various specifications of laptop brands. I have done feature engineering on data and have build different chine Learning models to achieve maximum accuracy and chosen best ML algorithm for best predictions. This project is build to predict price of laptop as per specifications.

Предсказание температуры стали, выплавляемой на металлургическом комбинате

This GitHub repository contains code for predicting the country destination of new Airbnb users using machine learning techniques on the "Airbnb New User Bookings" dataset from a Kaggle competition.