Your complete guide to understanding the language of artificial intelligence. This glossary breaks down complex AI and Machine Learning terms into simple, clear definitions.
Fine tuning a powerful base model is key for challenging tasks. In this guide, we adapt InceptionV3 for high-accuracy car recognition on the Stanford Cars dataset.
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.
Learn how to set up GPU acceleration on Windows using WSL2 and Ubuntu, install TensorFlow with GPU support, and compare CPU vs GPU performance for AI workloads.
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.