Sub-seasonal temperature and heatwave prediction in Central Europe with AI (linear and random forest machine learning models)

Gemstone Price Prediction - End to End ML Project with AWS deployment

Metis project 2/7

Data Models in R for Multiple Linear Regression and three models (Ridge, Lasso, and Elastic-Net), to predict Medicare claim costs of Type 2 diabetes patients with other diagnoses. We used Data from Entrepreneur’s Medicare Claims Synthetic Public Use Files (DE-SynPUFs) for our analysis.

House Price Prediction can help the customer to arrange the right time to Purchase a House. It is An - ML based Approach which Predicts the Estimated Price of Housing in Mumbai City.

Hybrid Ridge + LightGBM pipeline over 95k+ half-hourly demand records. Engineered Fourier seasonality, lag, and rolling-window features.

Multilable fast inference classifiers (Ridge Regression and MLP) for NLPs with Sentence Embedder, K-Fold, Bootstrap and Boosting. NOTE: since the MLP (fully connected NN) Classifier was too heavy to be loaded, you can just compile it with the script.

Practical Implementation of Linear Regression on Boston Housing Price Prediction

Forest Fire Data

This project is a machine learning application designed to predict the Fire Weather Index (FWI), a key indicator of forest fire risk, based on specific weather data from Algeria. The goal is to provide a tool that can help in anticipating and managing forest fires by understanding the relationship between weather conditions and fire probability.

In this series of notebooks, we will dive into each step of the data analysis process of a data set with some information about a list of cars and several attibutes, including their prices. So essentially we will develop a model to predict cars price.

This repository contains a collection of Machine Learning tasks, showcasing implementations of various algorithms, techniques, and concepts. From foundational methods like Linear Regression to advanced approaches using Scikit-Learn. Perfect for students and enthusiasts aiming to deepen their understanding of ML.

Practical Implementation of Linear Regression on Algerian Forest Fire Dataset.

A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net

A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets

It was a competition on KAGGLE for prediction on the most sales products on bikes via their features

Model Building and Testing using Ridge, Lasso and ElasticNet Methods

Advanced Regression model on Housing Data from Australia for my Upgrad - IIITB AI ML PG Course

In this project we are predicting the closing price of stocks by regression models