Topic: ridge-classifier Goto Github
Some thing interesting about ridge-classifier
Some thing interesting about ridge-classifier
ridge-classifier,A Real Time Expression Detector using Python and Machine Learning
User: ahasannn
ridge-classifier,Sub-seasonal temperature and heatwave prediction in Central Europe with AI (linear and random forest machine learning models)
User: bethweirich
ridge-classifier,Recognition of Persomnality Types from Facebook status using Machine Learning
User: dayfundora
ridge-classifier,This project focuses on analysing the performance of various Machine Learning models available in python's scikit-learn package when trying to predict wine classification
User: glopezv95
ridge-classifier,The analysis and classification of sleep, cardiovascular metrics, and lifestyle factors, for close to 400 fictive persons aiming to identify whether a potential client is likely to have a sleep disorder.
User: lisstasy
ridge-classifier,Analysis of the Avila bible dataset from the UCI repository using several machine learning algorithms.
User: m-pana
ridge-classifier,Project for the ING Lion's Den Competition. The goal of this project is to predict defaults of Big Lion Bankβs customers and I build logit, ridge, KNN and XGBoost models.
User: monika-kaczan
ridge-classifier,Our project utilizes machine learning models to predict cardiovascular diseases (CVDs) by analyzing diverse datasets and exploring 14 different algorithms. The aim is to enable early detection, personalized interventions, and improved healthcare outcomes.
User: prajwalp3
ridge-classifier,Fall 2020 - Computational Medicine - course project
User: ryanquinnnelson
ridge-classifier,We prepare a machine learning model that can be used to propose potential novel effective drugs to fight SARS-CoV-2, the virus responsible for COVID-19.
User: sagnik07
ridge-classifier,This repository serves as a platform to upload new code updates for my Master's Thesis (TFM), focused on the utilization of both supervised and unsupervised models on a dataset extracted from Spotify. It also includes a small fragment of my thesis. For more information, please contact me at:
User: smm1999
Home Page: https://www.linkedin.com/in/sergio-martinez-martinez/
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