Lazy Predict 2.0 to help you benchmark models without much code and understand what works better without any hyyper-parameter 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

Analysis and predictions of Traffic Accidents in the City of Madrid

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

Project is about predicting Class Of Beans using Supervised Learning Models

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

This is our Design Project for the semester.

Attrition prediction of Employees

Exploring a real-world dataset for regression analysis.

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.

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

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

Crop yields prediction using climatic factors

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.

LazyPredict - Comparer rapidement plusieurs modèles de Machine Learning