regression-algorithms

Collection of end-to-end regression problems (in-depth: linear regression, logistic regression, poisson regression) 📈

Using PyCaret to Predict Apple Stock Prices

Textual analysis of Investment themed subreddits to predict future stock returns

Data Mining project. In this project I tried to predict the number of likes of the videos through some machine learning models.

Examine the features of used cars posted on CarGurus at different times and locations to predict the selling price

ARTU: a second-order autoregressive reference method for solar radiation forecasting, with classical benchmarks (Persistence, Climatology, CLIPER, Exponential Smoothing).

Regression Model to predict the estimated hospitalisation for a patient to test a new drug for Diabetes using EHR data

Self-contained TypeScript Echo State Network (ESN) / Reservoir Computing library for online multivariate regression

In this project, we will evaluate the performance and predictive power of a model that has been trained and tested on data collected from homes in suburbs of Boston, Massachusetts.

My capstone project for Ryerson's Data Analytics, Big Data, and Predictive Analytics. The project I worked on was based on an open competition project called DengAI: Predicting Disease Spread. The objective of the project was to predict the total number of cases in the testing set of Iquitos, Peru & San Juan, Puerto Rico.

This repository contains files on Predict probability whether a given blight ticket will be paid

Welcome to my Data Science Portfolio! I'm Saravanan — an IITM Pravartak Certified Data Science Professional with practical experience building end-to-end ML and Deep Learning solutions across healthcare, finance, e-commerce along with NLP and GEN AI Domains. This portfolio highlights my work on real-world data-driven projects.

Analyzed the crime events that occurred in the City of Chicago, from 2001 till January 2017, using the data provided from Chicago Police Department’s CLEAR (Citizen Law Enforcement Analysis and Reporting) System

An R Companion for the Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, and Li (2005).

MLFND boston housing prices prediction project.

This repository consists of all the assignments i have done as a part of the neural networks lab which was a part of my curriculum.

In the project we built the following algorithms : Decision Tree Classifiier and Regressor, AdaBoost Classifiier , Gradient Boost Regressor

Determine concrete compressive strength

For the kaggle project - Loan Interest Rate Prediction, the repository contains the deployment details, project documentation file and project link.