The challenge is to build a system that can quickly and accurately separate annoying spam emails from the important ones in your inbox. The goal is to make sure you only see the emails you want to see and avoid the hassle of dealing with unwanted or potentially harmful messages.

Fast Wild Cluster Bootstrap Inference for Regression Models / OLS in R. Additionally, R port to WildBootTests.jl via the JuliaConnectoR.

Joint Analysis and Imputation of generalized linear models and linear mixed models with missing values

This repository contains all info relating to Data Science projects that I have completed.

This repository contains programs in the Python programming language using Module Streamlit.

The real estate price prediction with linear regression models.

Soil moisture analysis , prediction and decision making to irrigate or drain water from field using Machine Learning ,numpy ,pandas , sklearn , matplotlib , Gradient Boosting Regressor model, linear regression model .

This project involves predicting Total Yield Energy of a gas turbine using linear regression models.

Linear regressor ML model, with just numpy and pandas

My first solo data science project! A simple project built using linear regression to predict box office success for movies using data I scraped myself.

Collaborative work to learn streamlit and simple linear regression

Sure Tomorrow used machine learning to tackle challenges. I assessed its efforts to identify clients for marketing, forecast the chance of new client claims, and ensure better predictive performance, all while safeguarding client privacy without affecting previous models.

Data-Driven Decision Making: Selecting the Best Regression Model for E-commerce Sales

In this project, we leverage Deep Learning algorithms to build robust forecasting system that monitors the change in the demand side and aligns the supply side to make up for the inaccuracy of the forecasts and randomness in demand, helping retailers increase their inventory and planning efficiency.

The Project Market Value Predictor is a powerful tool developed to assist project managers, investors, and stakeholders in estimating the market value of their projects. By leveraging historical project data and employing machine learning techniques, this project aims to provide accurate and reliable predictions.

MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".

Predicting annual highest of sneakers on StockX

Linear Regression Machine learning The goal is to develop a model that can accurately predict salaries based on relevant features such as job title, years of experience, and education level.

PCA For Dimension Reduction And Visualization, Temperature-Yield Prediction Via Linear Regression, And Linear Fit Optimization Using Gradient Descent.

An API for managing chat completions, fine-tuning, payments, plans, and configurations.