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RL Course by David Silver - Lecture 6: Value Function Approximation
Taylor series | Chapter 11, Essence of calculus
Function Approximation | Reinforcement Learning Part 5
Why Neural Networks Can Learn Any Function
Intro to Taylor Series: Approximations on Steroids
Approximation Theory Explained | Neural Network Expressivity & Function Approx. in AI | Lec No 30
Can you really use ANY activation function (Universal Approximation Theorem)
The Universal Approximation Theorem of Neural Networks
Calculus 2 Lecture 9.9: Approximation of Functions by Taylor Polynomials
![DeepMind x UCL RL Lecture Series - Function Approximation [7/13]](https://i.ytimg.com/vi/ook46h2Jfb4/mqdefault.jpg)
DeepMind x UCL RL Lecture Series - Function Approximation [7/13]
Stanford CS234 Reinforcement Learning I Q learning and Function Approximation I 2024 I Lecture 4
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Last Updated: August 12, 2026
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