sklearn, tensorflow, random-forest, adaboost, decision-tress, polynomial-regression, g-boost, knn, extratrees, svr, ridge, bayesian-ridge

A python based project to predict the future prices of the top 10 trending cryptocurrencies using ML Algorithms like SVR, Decision Tree and LSTM with an interactive frontend using streamlit. Analysis using PowerBi and has DBMS connectivity.

A Machine Learning Model built in scikit-learn using Support Vector Regressors, Ensemble modeling with Gradient Boost Regressor and Grid Search Cross Validation.

Predicting house prices can help determine the selling price of a house in a particular region and can help people find the right time to buy a home.

Developed a predicting model for automatic bike sharing system using different machine learning and deep learning techniques like XGBoost, SVM, Decision Tree, Random Forest, and CNN and compared the accuracy of different algorithms. And applied grid search and random search to improve the accuracy, score, and reduced the random mean square error.

Regression Machine Learning Project

This repository presents a time series forecasting model for the stock market using SVR and LSTM to build a model that can predict the appropriate time for trading.

The Zomato Delivery Time Prediction Application is a machine learning-driven Flask web application designed to predict the estimated delivery time for food orders placed on the Zomato platform.

Stock Price Forecast App is based on Machine Learning. By providing number of days , we can predict trend in Stock Price. The frontend of App is based on Dash-plotly framework. Model is predicting stock price using Support Vector Regression algorithm. App can predict next 5-10 days trend using past 60 days data.

Utilized machine learning algorithms to analyze expenses and perform forecasting

Deciphering how customer's purchasing habits are influenced by wholesale pricing and examining its impact on final retail cost.

Machine Learning practice, Linear Regression, Multi-Linear Regression, Polynomial, Support Vector, Decission Tree, Random Forest.

Stock Prediction & Forecasting Using Machine Learning (SVR And LSTM)

This project addresses problem of early detection of Parkinson disease using Machine learning techniques

This is an assignment from my Machine Learning for Mechanical Engineers course that demonstrates an understanding in support vector regression using scikit-learn.

My programs for intuitively visualising the SVR machine learning algorithm.

Optimize fuel consumption in coal mine haulers using SVR techniques to improve efficiency, reduce costs, and minimize environmental impact.

Projet 5 - OpenClassRooms - Data Science

Time series forecasting using 8 different models

Revolutionize Mumbai's bus service with SVR-based population density prediction and NetworkX route optimization. Dynamic map visualization ensures efficient coverage of high-density areas, enhancing user-friendly public transportation .