Grad-CAM: definitions, applications and drawbacks
Kurious Fox Grad-CAM, which stands for Gradient-weighted Class Activation Mapping, is a technique used in artificial intelligence (AI) to understand…
machine learning in a random forest
A comparison between forward feature selection with cross-validation, forward selection guided by AIC/BIC, and Lasso regularization with Python Code
Forward feature selection with cross-validation incorporates cross-validation at each step to get a reliable estimate of how well…
Explainable AI (XAI) methods & Cheat Sheet
Explainable AI refers to methods and techniques that help humans understand and interpret the predictions and decisions made…
Enhancing Regression Models with Polynomial Features and L1 Lasso Regularization
Polynomial regression is a form of regression analysis in which the relationship between the independent variable and the…
Understanding Common Types and Characteristics of Data
Analyzing various data types and characteristics enhances model efficiency, aiding in pattern recognition and informed decisions. An example…
Key Roles of Transformation Matrices in Regression and PCA
Statistical Context: Projection and transformation matrices appear frequently in statistics, especially in regression and PCA, where they play…
Machine Learning and Deep Learning Free Online Courses
Basic probability & statistics Optimization & Background for Machine Learning and Deep Learning Deep learning: Introductory courses Advanced:…
Understanding Polynomial Regression: A Comprehensive Comic Guide with codes
Polynomial regression is a form of regression analysis in which the relationship between the independent variable and the…
Understanding Random Forests for Quantile Prediction with sklearn implementation
Random forests enhance predictive performance by allowing quantile predictions, offering insights into outcome variability. This method is vital…
Support Vector Machine + Python & R Codes
Support Vector Classifier (SVC) is a powerful algorithm for classification tasks, capable of handling linear and non-linear data…