Your complete guide to understanding the language of artificial intelligence. This glossary breaks down complex AI and Machine Learning terms into simple, clear definitions.
Practical Transfer Learning with ResNet50: build the pipeline, control overfitting, and evaluate on Stanford Cars with accuracy curves and a confusion matrix—no fine-tuning
Learn how to predict League of Legends match outcomes using logistic regression with PyTorch. An easy-to-follow introduction for beginners exploring practical machine learning concepts with gaming data.
Discover how linear regression works in machine learning and how to implement it using PyTorch. This beginner-friendly guide covers key concepts like predictions, loss, gradient descent, and model training—explained clearly with real-world analogies and visuals.
Evaluate your trained machine learning model and use it to make predictions. Understand key metrics like accuracy, precision, and recall in this hands-on guide!
Learn how to build a simple machine learning model in Python using the Iris dataset. In this part, we will step-by-step train our model.