Lazy Predict Nightly enables rapid benchmarking of machine learning models with just a few lines of code. It helps identify the best-performing algorithms on your dataset without requiring hyperparameter tuning.

The objective of the project is to perform advance regression techniques to predict the house price in Boston.

The objective of this project is to determine the risk of default that a client presents and assign a risk rating to each client. The risk rating will determine if the company will approve (or reject) the loan application

Utilizing LazyPredict, Feature Engine, Feature Tools: Narrow down base models automating various aspects of the eda process. Blog post at link.

This Program is for Prediction of Breast Cancer

Analysis and predictions of Traffic Accidents in the City of Madrid

Project is about predicting Class Of Beans using Supervised Learning Models

Binary Classification problem. Contains Classifiers from various AutoML libraries such as AutoGluon, FLAML, Lazypredict, & TPOT

This Program is for Prediction of Crop Recommendation based on Rainfall,Humidity,Amount of Potassium and Amount of Nitrogen

Containerised tool for machine learning model exploration using lazypredict

Predicting whether a customer is happy based on the results from a survey.

In this repository, I have displayed some of the datasets I've worked upon.

Predict patient satisfaction using machine learning based on doctor experience, reviews, fees, and wait times. Includes data prep and model comparison with LazyPredict.

Crop yields prediction using climatic factors

Exploring a real-world dataset for regression analysis.

Attrition prediction of Employees

This is our Design Project for the semester.

The main objective of this project is to utilize machine learning using the LazyPredict library to predict values of a specific column. The primary focus is on minimizing the error index (RMSE) to achieve the highest possible accuracy in our predictions.

The primary goal of this project is to conduct an Exploratory Data Analysis (EDA) in Formula 1 using Tableau and a pre-made MySQL database created with web scraping using Selenium. Our secondary objective is to develop a web page with Streamlit and apply machine learning with LazyPredict to predict events in Formula 1.