How To Evaluate A Neural Network Model Part I

How to evaluate a neural network model? We will break…

Bagging, Random Forest, And Boosting

Decision trees, bagging, random forest and boosting can all be applied to both regression…

Methods For High-Dimensional Problems In Linear Regression

Most of the relationships are not linear in the real world. However, linear model is an important model. It has distinct advantages in terms of its interpretability and predicts future data quite well. Also, if you use an…

How To Avoid Overfitting In Neural Networks

Most of the time, underfitting happens when the models or…

Underfitting, Overfitting, And The Bias-Variance Tradeoff

Understanding model fit is important for understanding the root cause for poor model accuracy. The ideal scenario when fitting a model is to find the “sweet spot” between underfitting and overfitting in order to make predictions…

ChatGPT, Resemble AI, Stable Diffusion, BARD, DALL-E, And Midjourney

Techniques to Combat Class Imbalance in Machine Learning

XGBoost, LightGBM, CatBoost

In the past, we did an overview of the tree-based methods. Today we will…

Measuring ROI For B2B Marketing And Sales

Attribution modeling doesn’t have to solely depend on…