I developed Machine Learning Software with multiple models that predict and classify AID362 biology lab data. Accuracy values are 99% and above, and F1, Recall and Precision scores are average (average of 3) 78.33%. The purpose of this study is to prove that we can establish an artificial intelligence (machine learning) system in health. With my…

Analytics Vidhya Hackathon

Fast-API base StockSeer-API uses different machine learning alogs to forecast closing stock prices.

A machine learning project that explores and predicts the prices of houses in Washington, USA

Explore ML mini-projects with Jupyter notebooks. Discover predictive analysis for commercial sales, leveraging regression models such as linear regression, decision trees, random forests, lasso, ridge, and extra-trees regressor.

Regression Using NeuralNet and CNN and a detailed analysis over the results obtained from regression techniques in ML and DL.

Loan Prediction Problem Analysis

Experiment testing the feasibility of individual bird recognition from audio recordings

In this project we will predict the time taken by NYC taxis to complete their trips using regression.

Explore and predict the used car price by building the machine learning model based on the existing data. Then examining the model between the actual price and the predicted price.

This is a end to end data science project where the flight fare has been predicted using Random Forest model.

This repository contains a machine learning project that predicts restaurant ratings. It leverages the Flask framework for model deployment, providing an interactive interface for real-time predictions.

Perform extensive Exploratory Data Analysis(EDA) on the Zomato Dataset. Building an appropriate Machine Learning Model that will help various Zomato Restaurants to predict their respective Ratings based on certain features deploy the Machine learning model via Flask

Predicting the bike count required at each hour for the stable supply of rental bikes.

Kaggle competition : prediction of the energy uses with machine learning

Explore machine learning for automotive testing optimization. Predictive analytics to reduce testing time and environmental impact.

Video transition time estimation with different regression techniques

2020 DACON CUP - 최종 2위

Naive, XGBoost, AdaBoost and other Regressors