Alpha Go: Machine Learning and Game Strategies

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Model-Based Deep Reinforcement Learning: Monte Carlo Tree Search

Explores model-based deep reinforcement learning, focusing on Monte Carlo Tree Search and its applications in game strategies and decision-making processes.

General Introduction into Artificial Neural Networks: part 3

Covers learning by rewards in deep reinforcement learning without math details.

First steps toward deep reinforcement learning

Explores the shift to deep reinforcement learning through neural networks for direct policy learning, bypassing Q-values and V-values.

Deep Q-Learning: DeepRL1.1

Covers Deep Q-learning in deep neural networks, its application in games, backpropagation, Q-values, and V-values.

Landscape and Generalisation in Deep Learning

Explores the challenges and insights of deep learning, focusing on loss landscape, generalization, and feature learning.

Chess Positions

Explores different chess positions and historical battle tactics, ending with a musical performance.

Creativity in Science

Explores the essence of science, creativity, and problem-solving through personal reflections and illustrative examples.

Positions in Chess: Understanding Strategies

Explores different chess positions and strategic gameplay, accompanied by musical interpretations of library books.

Introduction to Machine Learning

Provides an overview of Machine Learning, including historical context, key tasks, and real-world applications.

Autonomous Vehicles: Intelligence and Perception

Explores intelligence, perception, and AI applications in autonomous vehicles, emphasizing rational thinking and social intelligence.