In this project, I applied different regression models for rmse and mae on antenna dataset for predict signal strength.

This repository will work around solving the problem of food demand forecasting using machine learning.

Welcome to the Machine Learning Algorithms Implementation repository! This repository focuses on practical implementations of various regression algorithms using Python

Airline Fare Prediction using Regression

My graduation project on freezing casting data. Forecasting porosity with AI,

estimating the value of udemy finance & accounting course which target/label (which is continuous/data continuous) based on other variables which are features that influence the target/label with end-to-end process

A powerful stacked ensemble model for income prediction, combining GradientBoosting, AdaBoost, Bagging, Linear Regression, and Decision Trees. Achieves an impressive R² of 0.8761 on the RoS_sample_submission dataset.

Построение различных моделей линейной регрессии для предсказания курса доллара

Evaluating the performance and predictive power of a model. Cross questioned several concepts of ML for better understanding.

This repo hosts an end-to-end machine learning project designed to cover the full lifecycle of a data science initiative. The project encompasses a comprehensive approach including data Ingestion, preprocessing, exploratory data analysis (EDA), feature engineering, model training and evaluation, hyperparameter tuning, and cloud deployment.

In this project, I have developed a Machine Learning model to predict whether users will click on ads. By analyzing various characteristics of users who click on ads, we can gain valuable insights and optimize ad campaigns for better engagement.

Data Science Project (Regression for Numeric Data)

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

Analytics Vidhya hosts "JOB-A-THON" where over 7000+ enthusiasts got the opportunity to showcase their skills.

Comprehensive exploration of decision tree regressors, including data cleaning, model building, and performance evaluation on various datasets.

Predicting diamond prices helps buyers and sellers make informed decisions by understanding market trends and potential future values.

Previsão dos preços dos imóveis em Ihoa, USA com 4 modelos de regresão, feature engineering com SelectBest.

In this exploratory data analysis, we compare a dataset which consists of various features about renting of houses available on these renting platforms listed by owners of these houses, and try to derive some constructive conclusions by performing Descriptive statistics of the available features.

Decision Tree Regression using Python