Elastic Net Regression in R: Interactive Guide with an α–λ Playground
Learn Elastic Net regression in R by playing: mix Ridge and Lasso with alpha, slide lambda on real data, then fit and tune it with glmnet.
Introduction to Classification: Interactive Guide with Games and Quiz
Learn classification by playing: binary, multi-class and multi-label problems, real applications, the main algorithms and a live nearest-neighbour playground.
Logistic Regression in Python: Interactive Guide with a Threshold Lab
Learn logistic regression by playing: the sigmoid, log-odds, maximum likelihood and a live decision-threshold lab on real data, then code it from scratch in Python.
Decision tree classification in R
Decision Tree Classification in R: Interactive Guide with a Depth Slider
Learn decision trees by playing: entropy, Gini and information gain, ID3 vs C4.5 vs CART, and a live depth slider that shows overfitting, with rpart code in R.
Lasso Regression in R: Interactive Guide with a λ Playground and Quiz
Interactive R programming · Machine learning Lasso Regression in R, the game Learn Lasso by playing it. Seven short missions, a live λ playground built on real data, and a…
Knowledge Distillation
In this blog we will going to learn about the Knowledge distillation, its types and the implementation in python. Introduction Knowledge distillation is a technique in machine learning where knowledge…
Blending Classifier in Python
Blending is an ensemble machine learning technique that uses a machine learning model to learn how to best combine the predictions from multiple contributing ensemble member models. It is applicable…
Stacking Classifier in Python
In the era of Machine learning, no single algorithm performs best across all problems. This is where ensemble learning comes into play. A powerful technique that combines the strengths of…
Ensemble Learning algorithm and its types
An ensemble learning is a technique that combines the predictions from multiple machine learning algorithm to make more accurate prediction than any individual model. Types of Ensemble Learning Bagging (Ensemble…
Elastic Net regression in R
Ridge and Lasso regression are two powerful regularization techniques, but each comes with its own limitations: Ridge Regression (L2): Shrinks coefficients to prevent overfitting but never reduces them to zero…