Explore the first part of our series on sleep stage classification using Python, EEG data, and powerful libraries like Sklearn and MNE. Perfect for data scientists and neuroscience enthusiasts!

The goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

JSON Prompting is a technique for structuring instructions to AI models using the JavaScript Object Notation (JSON) format, making prompts clear, explicit, and machine-readable. Unlike traditional ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

ABSTRACT: This article explores the use of Support Vector Machines (SVM) for diagnosing diabetes based on fourteen medical and behavioral variables. Following a theoretical overview of diabetes and ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Build interactive web applications with Streamlit and Python Train Logistic Regression, Random Forest, and Support Vector Classifiers using scikit-learn Plot evaluation metrics for binary ...

Classified and clustered bank clients with respect to their user profile and decided if they should get credit. KNN & KMeans algorithms, K-Fold developed in C without libraries.

Everything on a computer is at its core a binary number, since computers do everything with bits that represent 0 and 1. In order to have a file that is "plain text", so human readable with minimal ...