🏡House Price Prediction, Artificial Intelligence course, University of Tehran

This repository contains implementations of popular machine learning algorithms including Support Vector Machine (SVM), Decision Tree, and Naive Bayes. Each algorithm is implemented separately, providing clear and concise examples of their usage for classification tasks.

Bike Sharing Demand Prediction By Supervised Machine Learning Algorithms Implementation On Seoul Bike Sharing Dataset

Zyfra is engaged in developing efficient solutions for heavy industry. as a Data Scientist we should be able to predict the amount of gold extracted or recovered from gold ore.

KOR: 개인 프로젝트. 머신러닝을 통해 테니스 선수 랭킹 예측. ENG: A personal project. Predicts rankings of tennis players using linear regression, decision tree regressor and random forest.

Exploring the impact of socioeconomic indicators on hardship in Chicago neighborhoods using machine learning. Leveraging Linear Regression, Decision Tree, random forest, and Agglomerative Clustering, the project identifies key factors—unemployment, lack of a high school diploma, and poverty—highlighting disparities in the dataset from 2008-2012

A decision tree implementation from scratch using Python, NumPy and pandas for four cases of real/discrete features/output.

An interactive web application that allows users to upload their datasets and dynamically select, train, and evaluate various machine learning models. The app provides comprehensive performance metrics and visualizations, making it easy for users to analyze their data effectively.

Implemented a Decision Tree Regressor, a Gradient Boosting Regressor, and a Hierarchical Clustering Algorithm.

Determining the Sales of Audi Cars across whole Europe by comparing the specifications as well as the price of some bestselling Models.

A project aimed at predicting variables of interest within the dataset.

Data Analysis and Machine Learning

Data in the social networking services is increasing day by day. So, there is heavy requirement to study the highly dynamic behavior of the users towards these services. The task here is to estimate the comment count that a post is expected to receive in next few(H) hours. Data has been scraped from one of the most popular social networking site…

The overall objective of this project is to critically analyze and develop the relationships of quantitative factors affecting life expectancy in 193 countries between 2000 and 2015 that underlie changes in life expectancy. The importance of predicting life expectancy arises because of its important role as an indicator of the overall health.

A machine learning application aimed at predicting employee salaries based on various features such as experience, education level, location, etc. By using different models and techniques, the project seeks to present an optimized model for salary predictions.

Future Stock Prediction Model

Demystifying ~400K layoffs to analyze underlying causes and predict future trends of layoffs by different companies.

This Project deals with determining the product prices based on the historical retail store sales data. After generating the predictions, our model will help the retail store to decide the price of the products to earn more profits.

Predicting breast cancer survival using machine learning models