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

No description provided.

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.

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.

This is First Project of Machine Learning by me

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

Forest Fire Data

Practical Implementation of Linear Regression on Boston Housing Price Prediction

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.

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

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.

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

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

Using OLS regression (and Ridge and Lasso to compare), we worked on a project that uses a dataset to predict housing prices based on user inputs on house details.

Machine learning project predicting house prices using the King County dataset with Scikit-learn pipelines and regression modeling.

End-to-end machine learning regression model for predicting housing prices in Bengaluru, with Heroku deployment.

Regression models(lasso, ridge, DT) using NumPy.

Machine Learning Algorithms

This repository showcases an array of data science notebooks focused on exploratory data analysis (EDA), data curation, and the application of diverse machine learning techniques to a variety of datasets. Each project highlights detailed analysis, visualization, and algorithmic insights, offering both depth and breadth in data science methodologies

ML: Write a data science blog to show case communication skills. Predict Airbnb prices using ridge regression.

Exploring World Development Indicators: Identifying relationship between Health Indicators using Linear Regression & Classification of Income Group based on Health Indicators using Logistic Regression.

Building Advanced regression models (Lasso and Ridge) for house price prediction in the Australian market

As part of the UCSanDiego online course "Machine Learning Fundamentals"