How-To Geek on MSN

Your Excel regression is probably a mess—here's how Python fixes it

Uncover the hidden pitfalls of Excel regression and learn why Python is the key to unlocking clean, efficient data analysis.
GitHub

c-lasso: a Python package for constrained sparse regression and classification

c-lasso is a Python package that enables sparse and robust linear regression and classification with linear equality constraints on the model parameters. For detailed info, one can check the ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...
LinkedIn

A Step-by-Step Walkthrough: Implementing PSM in Python

In previous article, we learned the magic of Propensity Score Matching (PSM) —how it finds "statistical twins" to mimic a randomized experiment. Now, it's time to open the toolbox and perform the ...
Visual Studio Magazine

Linear Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...
GitHub

Log Neural Controlled Differential Equations (ICML 2024)

This repository now supports Structured Linear Controlled Differential Equations (SLiCEs), which replace the non-linear vector fields of NCDEs and Log-NCDEs with structured linear vector fields, ...
LinkedIn

Mastering Logistic Regression: The Complete Guide with Python Code

In machine learning, classification tasks are everywhere spam detection, medical diagnosis, credit scoring, churn prediction, and more. Among the foundational algorithms for classification, Logistic ...
C&EN

Optimized Collective Variable for Collapse Transition in Linear Hydrophobic Polymers: Importance of Hydration Water and End-to-End Distance

School of Chemical Sciences, Indian Association for the Cultivation of Science, Jadavpur, Kolkata 700032, India ...
PNAS

Linear Recursive Feature Machines provably recover low-rank matrices

Understanding the mechanism of how neural networks learn features from data is a fundamental problem in machine learning. Our work explicitly connects the mechanism of neural feature learning to a ...
Nature

Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

We present a gene-level regulatory model, single-cell ATAC + RNA linking (SCARlink), which predicts single-cell gene expression and links enhancers to target genes using multi-ome (scRNA-seq and ...
Frontiers

nPCA: a linear dimensionality reduction method using a multilayer perceptron

Background: Linear dimensionality reduction techniques are widely used in many applications. The goal of dimensionality reduction is to eliminate the noise of data and extract the main features of ...