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A machine learning project that predicts diabetes diagnosis using K-Nearest Neighbors (KNN) classification with SMOTE-based class balancing.

This project implements a machine learning solution to predict the survival of passengers aboard the RMS Titanic. The model uses a Random Forest Classifier and achieves 86.03% accuracy on the validation set. The project includes comprehensive data preprocessing, feature engineering, and exploratory data analysis.

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UK Weather Mapping delivers real-time temperature, precipitation, and wind insights for 30+ UK cities by combining OpenWeatherMap data with Python geospatial tools. The repo includes static Cartopy visualisations, an interactive Folium web map, and a narrative report explaining the data pipeline, API integration, and design decisions.

Predict hourly Ola bike ride demand using engineered time/holiday features and tuned linear models to achieve ~56 MAE; this notebook guides cleaning, exploration, and modeling.

A fast-paced geography trivia game that challenges players to identify world flags, track streaks, and climb the leaderboard. The app pairs a polished Tailwind UI with a custom Express API that keeps the flag options fresh and prevents quick repeats, making every run feel like a world tour.

A Python-based data analysis project analyzing Zomato restaurant data. Explores restaurant types, ratings, pricing, online ordering patterns, and customer preferences through statistical analysis and visualizations using Pandas, Matplotlib, and Seaborn.

Beautiful, minimal desktop app to check today's weather by city.

A beautiful Python based recipe explorer app with a modern Tkinter GUI. Search recipes by country or category, view ingredients and instructions, with smooth scrolling and fast image loading powered by TheMealDB API.

Simple breast cancer binary classifier using the Wisconsin CSV dataset. The script preprocesses the data (drops id/unused columns, encodes labels, scales features), trains a small Keras neural network, and outputs training/validation loss & accuracy plots plus a confusion matrix. Run with data.csv in the same folder.

Analyzing and visualizing air pollution patterns over time.

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Solar Power forecasting for a Solar Power System is a very active research field, as reliable information about the future power generation allow for a safe operation of the power grid and helps to minimize the operational costs. Deep Learning algorithms have shown to be very powerful in forecasting tasks, such as economic time series or speech recognition. Up to now, Deep Learning algorithms have only been applied sparsely for forecasting renewable energy power plants. By using different Deep Learning Algorithms, such as RNN,LSTM with different Feature extraction method like PCA,1D CNN , Auto encoders , My motive is to show the forecast strength of these algorithms compared to a standard MLP and traditional machine learning model in forecasting the energy output of 21 solar power plants.

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This project aims to predict the price of laptops based on their technical specifications using various machine learning models. The dataset includes attributes like brand, processor, RAM, memory type, GPU, screen size, and operating system.

A machine learning project that detects spam SMS messages using natural language processing techniques. The model analyzes text messages and accurately classifies them as spam or legitimate (ham).

This project presents a comprehensive car price prediction model using machine learning techniques. The dataset is carefully explored and preprocessed, including handling missing values, encoding categorical features, and scaling numerical data. Visualizations are provided to understand key relationships and trends in car features and prices.

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This project predicts Parkinson's disease using machine learning models.

This project is aimed at predicting the likelihood of coronary heart disease (CHD) in individuals over the next ten years using Logistic Regression.

This is a Address Book using the MERN stack. The application will enable users to add, remove, edit and view addresses.

This project is a fundraiser platform developed using the MERN stack.

The Expense Tracker System is a robust web application designed to help users manage their expenses efficiently. Built using the MERN stack (MongoDB, Express, React, Node.js), this system allows users to track their income and expenses, categorize transactions.

This project leverages computer vision and machine learning to interpret hand gestures and movements, enabling interaction with volume device of your pc without the need for physical controllers.

Free Dictionary app. Search a word and you will get the meaning.

Welcome to the Book Library project! This is a simple web application built with React that allows users to browse and manage a library of books.

Explored different attributes of Boston housing dataset then a part of dataset was used to train the linear regression algorithm after that trained model was used to give predictions on remaining part of dataset.

This website fetches data (joke) from an external API and displays it on the screen. I have used React completely to base this website. Each time we reload the page and click the button, a new joke fetched and rendered on the screen by React.

Scraped weather data using Python and get reminders on telegram inbox. If the weather condition is rainy or cloudy this program will send an “umbrella reminder” to your inbox reminding you to pack an umbrella before leaving the house. Scraped the weather information from using open weather api and requests libraries in python