21–30 of 41 posts
Would this teach transformers? Or is that something else? Also any tips for finding a study group for learning the large language models? I can’t seem to self motivate.
Before jumping into Deep Reinforcement Learning I highly recommend doing the Reinforcement Learning course by David Silver [1]. [1] https://www.deepmind.com/learning-resources/introduction-to-...
No code, coding assignments, math problems or coding problems.
Very little RoI.
I watched them all from start to finish. I had a superficial, shallow "understanding" but no real knowledge.
The best (very short book) to learn Deep RL is the one by Zai, Brown from Manning.
And keep the classic Sutton, Barto near. That's it.
If you want a video course that closely follows the book with quizzes and assignments, check out UofAlberta's MOOC on Coursera.
(Hugging Face also has a new Deep RL course taught by Simonini. You could check that out, but I haven’t seen it.)
Would this teach transformers? Or is that something else? Also any tips for finding a study group for learning the large language models? I can’t seem to self motivate.
Maybe this would help you differentiate: GPT-3, DALL-E 2 etc. uses transformers, while AlphaGo, OpenAI Five etc. uses Deep Reinforcement Learning. They are not mutually exclusive, but just different things.
Transformers are being used in Deep RL for at least months.
Try these: https://scholar.google.com/scholar?q=transformer+deep+reinfo...
Before jumping into Deep Reinforcement Learning I highly recommend doing the Reinforcement Learning course by David Silver [1]. [1] https://www.deepmind.com/learning-resources/introduction-to-...
Before jumping into Deep Reinforcement Learning I highly recommend doing the Reinforcement Learning course by David Silver [1]. [1] https://www.deepmind.com/learning-resources/introduction-to-...
Nice resource, but still 10+ hours of video and nothing else. No code, coding assignments, math problems or coding problems. Very little RoI. I watched them all from start to finish. I had a superficial, shallow "understanding" but no real knowledge. The best (very short book) to learn Deep RL is the one by Zai, Brown from Manning. And keep the classic Sutton, Barto near. That's it. If you want a video course that cl…
Sutton and Barto is the best start for foundations. Start there.
Enrolled! Went through the detailed lesson plan and you have done a great job structuring the course. I am looking forward to doing it over the weekend. One suggestion: Instead of naming all the Jupyter notebooks "coding_exercise.ipynb", maybe name them differently? That way, they won't overwrite the previous download.
Good catch. I can imagine that this is annoying. I have put it in my todo. I hope you enjoy the course over the weekend.
I haven't looked deeply enough, but does this course use a higher-level 'package' such as OpenAI Gym or teach at a lower-level? (Is lower-level stuff even possible...)
Before jumping into Deep Reinforcement Learning I highly recommend doing the Reinforcement Learning course by David Silver [1]. [1] https://www.deepmind.com/learning-resources/introduction-to-...
To be honest though, the practical side of things of RL can be a hit-and-miss in terms of "fun" depending on the person. It requires a lot of manual hand tuning, reward shaping, hyperparameter tuning, and general trial-and-error to make an agent do a seemingly simple-enough task, and these tricks are more heuristically and haphazardly done than what you would expect from more "conventional" programming. It is fun for…
My experience matches yours. Recently, I was trying to solve an optimization problem using Deep RL. As usual, I had to run many experiments over several days using various tricks and hyperparameters. Finally, it turned out something related to the symmetry of the action space made a huge difference in learning. Anyhow, the experimentation stage requires a certain discipline and feels tedious at times. But the moment…
Earlier quoted context omitted.
Good catch. I can imagine that this is annoying. I have put it in my todo. I hope you enjoy the course over the weekend.
Thank you for doing this! I haven't looked deeply enough, but does this course use a higher-level 'package' such as OpenAI Gym or teach at a lower-level? (Is lower-level stuff even possible...)
The situation looks different for Deep RL algorithm. You can implement them from scratch yourself using Tensorflow or any other similar library. Otherwise, you could just use a higher-level library like RLlib which implements the algorithm using modular components and exposes hyperparameters as configuration parameters.
In many real world use cases, all one needs to do is to use RLlib's implementation and then tune the hyperparameters. In that way RLlib is to Deep RL what Keras is to Deep Learning.
This course uses RLlib. Does that answer your question?