LazyPredict - Comparer rapidement plusieurs modèles de Machine Learning
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Updated
Jul 13, 2024 - Jupyter Notebook
LazyPredict - Comparer rapidement plusieurs modèles de Machine Learning
Predicting whether a customer is happy based on the results from a survey.
Practical exercise using the "Richter's Predictor: Modeling Earthquake Damage" competition on DrivenData
Lazy Predict 2.0 to help you benchmark models without much code and understand what works better without any hyyper-parameter tuning.
Trabalho desenvolvido para o SoulMaster Upskilling da Soulcode Academy que busca resolver um problema específico na área de educação com o uso de Análise Preditiva com Vertex AI e LazyPredict.
Predict home prices using regression, optimizing for R2 and RMSE metrics to create a robust model with minimal prediction deviation.
The projects aim is to find the to best ML algorithm evaluated on its efficiency in predicting whether homes should be classified as expensive or not expensive.
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.
Exploring a real-world dataset for regression analysis.
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.
This Program is for Prediction of Crop Recommendation based on Rainfall,Humidity,Amount of Potassium and Amount of Nitrogen
Project is about predicting Class Of Beans using Supervised Learning Models
This Program is for Prediction of Breast Cancer
This is our Design Project for the semester.
Testing LazyPredict performance
The objective of the project is to perform advance regression techniques to predict the house price in Boston.
Attrition prediction of Employees
Utilizing LazyPredict, Feature Engine, Feature Tools: Narrow down base models automating various aspects of the eda process. Blog post at link.
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