#linearRegression

Ivaylo Ivanoviv_ivaylo
2026-01-29

This same idea scales up in modern AI systems:
learn from data → predict.

Linear regression isn’t about complexity.
It’s about building intuition — and realizing you can understand how intelligent systems learn.

Mahmoud Zaltzalt
2026-01-18

What actually powers LinearRegression under the hood? This piece digs into the hidden engine behind it and why that internal design matters for your models.

Read More: zalt.me/blog/2026/01/hidden-li

AI Daily Postaidailypost
2025-12-07

Before diving into deep learning hype, remember the power of classic algorithms. Linear regression, decision trees, and thoughtful feature engineering still drive real‑world analytics and revenue. Master these fundamentals and your neural nets will perform better, faster, and cheaper. Curious how the basics outpace the buzz? Read on.

🔗 aidailypost.com/news/master-fu

IB Teguh TMteguhteja
2025-10-31

Unlock the secrets of Linear Regression Machine Learning! A comprehensive guide for beginners. Dive into predictive modeling and data analysis.

teguhteja.id/linear-regression

Hacker Newsh4ckernews
2025-05-08
cathillcathill
2025-04-15

Is machine learning merely a form of curve-fitting?

Python Job Supportpythonjobsupport
2025-04-10

Forecasting in Excel using Linear Regression

Forecasting Hello Friends, In this video, you will learn how to do the sales forecasting in Excel. We have ... source

quadexcel.com/wp/forecasting-i

Journal of Plant Ecologyjpecol
2025-03-30

Bingqian Su et al. established a based on growth and its driving factors on China’s , developed considering , , and using and three .
doi.org/10.1093/jpe/rtae104

Distribution of study sites on the Loess Plateau in the synthesis.
Amit Kamalbhai Dhananiamitdhanani2019
2025-02-15

How to Train Machine Learning model withou ML Library with simple Python code a internal work ? then follow below link - it has video also

amitdhanani.in/2025/02/15/how-

Eric Maugendre about datamaugendre@hachyderm.io
2025-02-02

@data @datadon 🧵

Accuracy! To counter regression dilution, a method is to add a constraint on the statistical modeling.
Regression Redress restrains bias by segregating the residual values.
My article: data.yt/kit/regression-redress

#bias #modeling #dataDev #AIDev #modelEvaluation #regression #modelling #dataLearning #linearRegression #probability #probabilities #statistics #stats #correctionRatio #ML #distributions #accuracy #RegressionRedress #Python #RStats

Eric Maugendre about datamaugendre@hachyderm.io
2025-01-30

@data @datadon 🧵

How to assess a statistical model?
How to choose between variables?

Pearson's #correlation is irrelevant if you suspect that the relationship is not a straight line.

If monotonic relationship:
"#Spearman’s rho is particularly useful for small samples where weak correlations are expected, as it can detect subtle monotonic trends." It is "widespread across disciplines where the measurement precision is not guaranteed".
"#Kendall’s Tau-b is less affected [than Spearman’s rho] by outliers in the data, making it a robust option for datasets with extreme values."
Ref: statisticseasily.com/kendall-t

#normality #normalDistribution #modeling #dataDev #AIDev #ML #modelEvaluation #regression #modelling #dataLearning #featureEngineering #linearRegression #modeling #probability #probabilities #statistics #stats #correctionRatio #ML #Pearson #bias #regressionRedress #distributions

Eric Maugendre about datamaugendre@hachyderm.io
2024-12-29

"In real life, we weigh the anticipated consequences of the decisions that we are about to make. That approach is much more rational than limiting the percentage of making the error of one kind in an artificial (null hypothesis) setting or using a measure of evidence for each model as the weight."
Longford (2005) stat.columbia.edu/~gelman/stuf

#modeling #nullHypothesis #probability #probabilities #pValues #statistics #stats #statisticalLiteracy #bias #inference #modelling #regression #linearRegression

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