This article uses a fruit basket analogy to explain key concepts in machine learning evaluation metrics, including recall, precision, and F1 score, making it easier to understand how these metrics relate to identifying true positives, false positives, and false negatives.
If you've ever wondered how your favorite apps seem to know what you like, or how self-driving cars navigate the streets, you're in the right place. In this article, we'll break down the basics of machine learning in a friendly and approachable way, making it easy for anyone to understand.
An overview of neural networks and deep learning - introductory quick read-up, including their use cases, and pros and cons for each technique.
Summary of the ideal use cases for models implemented in the scikit-learn Python library for machine learning.