Microservicio que predice la temperatura y humedad usando Arima y RandomForestRegressor

Prepr's Machine Learning Challenge

Dataset of the real-time election results of the 2019 Portuguese Parliamentary Election. Dataset describing the evolution of results in the Portuguese Parliamentary Elections of October 6th 2019. The data spans a time interval of 4 hours and 25 minutes, in intervals of 5 minutes, concerning the results of the 27 parties involved in the electoral…

Predicting Math Scores for Brazilian high School National Exams

Regression - Bulldozer Sales Price - Kaggle Competition

A machine learning project to detect the fake news.

Prediction of car prices using data from sahibinden.com

Simple Application for predicting price of the flight. It uses sklearn pipeline to perform preprocessing , feature selection and feature engineering and model building .The pipeline object is saved in a pickle file and used in the flask application for prediction

Code templates for data prep and different ML algorithms in Python.

Построение различных моделей линейной регрессии для предсказания курса доллара

For Udacity Data Science Nanodegree. Finds top predictors of high review scores

In this project, I have used Random forest Regressor and done a lot of data preprocessing on raw data finally get an accuracy of approximately 81 percent. This project mainly focuses on data preprocessing.

Use Machine Learning models to Predict Salary based on metadata from HR.

The goal of this problem is to predict the Price of an Old car based on the variables provided in the data set.

🚘 Car-Choice 🚔 is a used car price prediction web app.

The current study deals with the exploration and preparation of a dataset concerning bicycle rentals in Washington D.C, in order to predict the total number of rental bicycles per hour.

I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.

Evaluation of the Models (Regression and Classification)