This repo is meant to serve as a detailed guide for Machine Learning/AI interviews.
ML-algorithms from scratch using Python. Classic Machine Learning course.
Deepfake Detector is an AI/ML model designed to detect AI-generated or manipulated images.
JABACAT-created machine learning library from scratch.
ML Concept Implementation in C#
These are my notes for machine learning
A collection of practical machine learning concepts and implementations focused on enhancing understanding through hands-on examples.
A collection of core Machine Learning algorithms implemented from scratch using only NumPy. This project focuses on understanding the inner workings of ML models without relying on libraries like scikit-learn, TensorFlow, or PyTorch.
Retail Recommendation System uses deep neural networks to deliver personalized product recommendations based on customer behavior and product data, helping retailers boost engagement, optimize inventory, and drive growth.
Screwing around with Machine Learning
Add a description, image, and links to the machine-learning-algorithms-from-scratch topic page so that developers can more easily learn about it.
To associate your repository with the machine-learning-algorithms-from-scratch topic, visit your repo's landing page and select "manage topics."