Series Path · 2 parts
Beyond Supervised Learning
Training paradigms beyond fixed labelled datasets — reinforcement learning fundamentals and active learning with influence-based sample selection.
~28 min total·2 articles
Start from Part 1Curriculum — 2 parts
- 01
Complete Guide to Reinforcement Learning
Reinforcement Learning (RL) is a paradigm of machine learning where an agent learns to make decisions by interacting with an environment to maximize cumulative…
8 min read - 02
Active Learning Influence Selection: A Comprehensive Guide
Active learning is a machine learning paradigm where the algorithm can interactively query an oracle (typically a human annotator) to label new data points.…
20 min read