Predict sales prices and practice feature engineering, RFs, and gradient boosting

Builded a model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.

Cross-validation, knn classif, knn régression, svm à noyau, Ridge à noyau

This Repository contains scratch implementations of the famous metrics used to evaluate machine learning models.

Flight delay prediction based on the 2007 entries from the US domestic flight database

Regression - Bulldozer Sales Price - Kaggle Competition

A data mining project to analyse Airbnb's data of Berlin for the year 2020 using KDD

Built a few forecasting models to determine the demand for a particular product.

A Preprocessing, Analytical and Modeling Case Study using Supervised ML Models

Housing Price Prediction Challenge

profit estimation of companies with linear regression

ML implementations in Multi-scale model for lignin biosynthesis in Populus Trichocarpa

All things around ... Regression

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Predicting total ride duration of taxi trips in New York City, the training set (contains 1458644 trip records)

Power Transformer works best on linear model and The Power Transformer actually automates this decision making by introducing a parameter called lambda. It decides on a generalized power transform by finding the best value of lambda

Ml model to predict car prices based on certain parameters.