Determining the housing prices of California properties for new sellers and also for buyers to estimate the profitability of the deal.

Explorando as notas do ENEM de 2018 tal como análise sobre o gabarito x acertos x erros e criando um Machine Learning para adivinhar as notas.

Future Stock Prediction Model

Data Analysis and Machine Learning

Machine Learning Examples for Beginners

Third Assignment in 'Practical topics in Machine Learning' course by Dr. Kfir Bar at Bar-Ilan University

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.

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.

A model was built to predict the total insurance claim amount payable by the insurance company using machine learning techniques such as regression in python.

Applying data mining algorithms to the Stack Overflow Developer Survey dataset using Python

Machine learning project to predict NYC property prices.

In this project, I am applying your frequentist inference and regression modelling skills to different datasets. I applied several machine learning algorithms and try to answer research questions of related problems and also perform data visualization to justify my results.

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

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

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…

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

Using a dataset provided by Airbnb, analysis and predictions will be made to understand what effects the total price of an Airbnb

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

Predicting using Decision Tree Regressor and Random Forest Regressor