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How to Validate Your Data With Statistical Tests in Python

Statistical testing in Python offers a way to make sure your data is meaningful. It only takes a second to validate your data ...

Cai Cai's Machine Learning Sklearn Class: Understandable from Scratch, from Model Invocation to Practical Implementation

The design of sklearn follows the "Swiss Army Knife" principle, integrating six core modules: Data Preprocessing: Similar to ...
Visual Studio Magazine

Kernel Ridge Regression with Cholesky Inverse Training Using C#

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single ...
IEEE

A multidimensional indicator prediction assessment method based on time series and multiple linear regression model

Abstract: This paper focuses on a multidimensional indicator prediction assessment method based on time series and multiple linear regression modelling. Through in-depth analysis of relevant data, ...
GitHub

OpenData4Sciece/glm-learning-project

Pierre-Henry Soria — An Extremely Passionate Data Scientist who loves automating content creation efficiently with meaningful data! Also a true roquefort 🧀, ristretto ☕️, and dark chocolate lover! 😋 ...
GitHub

glm-python

Developed an end-to-end customer churn prediction ML pipeline using Python, pandas, and scikit-learn. Implemented and trained a logistic regression model, then deployed it as a REST API service using ...
IEEE

Fully Homomorphically Encrypted Linear Regression Using CKKS

Abstract: In this paper, we consider the solution of encrypted linear regression using Homomorphic Encryption. We propose a method in which each mathematical operation is performed over encrypted real ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...