Junior faculty are often told to protect their time, but nobody provides instructions for how to do so. As an assistant professor at a public university, I have struggled to balance my course load, my ...

This video is an overall package to understand L2 Regularization Neural Network and then implement it in Python from scratch. L2 Regularization neural network it a technique to overcome overfitting.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

Abstract: This paper proposes a production decision analysis model based on decision tree and Bayesian optimisation, aiming to optimise the decision-making in the production process of enterprises.

Learn how to implement the AdaMax optimization algorithm from scratch in Python. A great tutorial for understanding one of the most effective optimizers in deep learning. Russian lawmaker issues ...

Abstract: The decision tree algorithm is an effective machine learning technique, but it cannot uncover causal relationships within data. To overcome this limitation, the causal decision tree was ...

While the New York Giants had, at least on paper, a successful draft, there was one thing that they didn’t do that might qualify as a headscratcher: not selecting multiple offensive linemen in the ...

A comprehensive implementation of a Decision Tree classifier using the ID3 algorithm, featuring advanced visualization capabilities and support for multiple datasets. Built entirely from scratch ...

I had a very interesting discussion about decision trees recently and I thought it worth my time to explore use cases. A simple terminal-based decision tree implementation that processes structured ...

Objective: To develop a decision tree model using clinical risk factors to predict massive pulmonary hemorrhage (MPH) and MPH-related mortality in extremely low birth weight infants (ELBWIs). Method: ...