Tag: Blog

Effective Python (26) — Use multiple inheritance only for mix-in utility classes

by Yuan Ma

Python is an object-oriented language with built-in facilities for making multiple inheritance tractable. However, it's better to avoid multiple inheritance altogether. If you find you yourself desiring the convenience and encapsulation that comes with multiple inheritance, considering writing a mix-in instead. A mix-in is a small class that only defines a set of additional methods … Continue reading Effective Python (26) — Use multiple inheritance only for mix-in utility classes

Open courses recommendation

by Yuan Ma

Reinforcement Learning [Berkley] CS 294: Deep Reinforcement Learning, Spring 2017 [MIT] 6.S094: Deep Learning for Self-Driving Cars, Spring 2017 [Stanford] CS231n: Convolutional Neural Networks for Visual Recognition, Winter 2016. Self-Driving [Udacity] SIRAJ RAVAL’S DEEP LEARNING – Nanodegree fundation program [Udacity] Self-Driving Car Engineer Nanodegree Others [Youtube] Bay area deep learning school. McGill Artificial Intelligence Society

Reference for Reinforcement Learning

by Yuan Ma

Papers RL for game playing Newest (in recent 2 years): Heinrich, Johannes, and David Silver. “Deep Reinforcement Learning from Self-Play in Imperfect-Information Games” (2016). Finn, Chelsea, Tianhe Yu, Justin Fu, Pieter Abbeel, and Sergey Levine. “Generalizing Skills with Semi-Supervised Reinforcement Learning.” arXiv (2016) Classic: Mnih, Volodymyr, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan … Continue reading Reference for Reinforcement Learning