Feb. 4, 2022, 7:03 p.m. | NandaKishore Joshi

Towards Data Science - Medium towardsdatascience.com

Part 1 — Building a deep Q-network to play Gridworld — DeepMind’s deep Q-networks

In this article let’s build a Deep Q-network similar to the DeepMind’s Atari agent to play Gridworld problem. We will build virtually the same system the DeepMind did from scratch to understand the Deep Q-network in detail. We will understand the drawbacks of vanilla Deep Q-network and come up with the clever ways to overcome them.

We have seen how to build a simple Deep Reinforcement …

building data science deep learning deepmind deep-q-learning machine learning network networks part reinforcement learning

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Data Engineer - Takealot Group (Takealot.com | Superbalist.com | Mr D Food)

@ takealot.com | Cape Town