Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.

Related tags

Machine Learninglinear-regressionregressionregularizationridge-regressionlasso-regressionknn-regressionknn-classification
Overview

Linear Models

Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers.

Linear Regression

  • Optimizer: Square Least
  • Regularizer: None

Lasso Regression

  • Optimizer: Gradient Decent
  • Regularizer: L1

Ridge Regression

  • Optimizer: Gradient Decent
  • Regularizer: L2
Owner
Keivan Ipchi Hagh
ISTP-A | Kaggle Contributor | ML Enthusiast
Keivan Ipchi Hagh
GitHub Repository
This is a Machine Learning model which predicts the presence of Diabetes in Patients

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Educational python for Neural Networks, written in pure Python/NumPy.

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Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

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A linear regression model for house price prediction

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Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.

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Backprop 227 Dec 10, 2022
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A python library for Bayesian time series modeling

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Reggy - Regressions with arbitrarily complex regularization terms

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