SUTD 2020 10.008 Hands-on Activity Code Dump
Predictive machine learning application estimating employee compensation baselines via Scikit-Learn and a Flask API microservice.
A diabetes prediction model trained and tested on the basis of machine learning regression model which also calculates the root mean square error of the prediction.
Machine Learning project that predicts medical insurance costs using Polynomial Regression and Streamlit.
It is work about which we want to see the relation of characteristics with body fat and try to forecast the amount of it
A machine learning approach to the inverse design of microstrip patch antennas by predicting optimal physical dimensions from desired performance metrics.
Excel implementation of statistical models for optimal yaw angle estimation in tandem wind turbines, maximizing power output under wake interaction.
The purpose of this work is the modeling of the wine preferences by physicochemical properties. Such model is useful to support the oenologist wine tasting evaluations, improve and speed-up the wine production. A Neural Network was trained using Tensorflow, which was later tuned in order to achieve high-accuracy quality predictions.
This project focuses on developing a machine learning model to predict the price of diamonds based on various attributes. By analyzing a dataset that includes information about the carat weight, cut, color, clarity, and other factors, we aim to create a model that can accurately estimate the price of diamonds.
Data Analysis and Machine Learning Project
In this project I have implemented 14 different types of regression algorithms including Linear Regression, KNN Regressor, Decision Tree Regressor, RandomForest Regressor, XGBoost, CatBoost., LightGBM, etc. Along with it I have also performed Hyper Paramter Optimization & Cross Validation.
CSCI 4371: Machine Learning - Final Project
🏏 IPL Score Predictor – Real-time first-innings batting score forecasting web app using Lasso Regression. Predict final score based on teams, venue, current runs/wickets, overs, and recent performance. Built with Streamlit.
End-to-end machine learning application for laptop price prediction built with scikit-learn and deployed using Streamlit. The project demonstrates data preprocessing, feature engineering, model training, and interactive cloud deployment.
My Notes as i dive into Machine Learning , Datascience , Deployment , Devops
Predict the price of a used car in the Greater Cleveland area.
R codes for performing Regression analysis
An app allowing you to predict the best possible time possible for a game speedrun.
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