RL-Adventure-2
Made-With-ML
| RL-Adventure-2 | Made-With-ML | |
|---|---|---|
| 3 | 51 | |
| 3,211 | 36,004 | |
| - | - | |
| 0.0 | 6.8 | |
| 5 months ago | 5 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| Apache License 2.0 | MIT License |
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RL-Adventure-2
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Why does this implementation uniformly initialize the final layer off their network
I am following this implementation of ddpg and found this code -
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RuntimeError: Trying to backward through the graph a second time (or directly access saved tensors after they have already been freed)
Also, modified this code - https://github.com/higgsfield/RL-Adventure-2/blob/master/1.actor-critic.ipynb
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[N] 20 hours of new lectures on Deep Learning and Reinforcement Learning with lots of examples
Lecture 8: Policy gradient methods. (slides, code, theory, video)
Made-With-ML
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[D] How do you keep up to date on Machine Learning?
Made With ML
- Open-Source Production Machine Learning Course
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Advice for switching careers within analytics
- Develop a (simple!) ML project and apply MLOps best practices to it. Ask Chat GPT all of your MLOps questions. I've joined this MLOps community and it has been very helpful to know what path to follow in order to be better at MLOps, thanks to them I arrived at madewithml, but I haven't done it yet. But it covers all the MLOps side.
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Recommendation for MLOps resources
Hey, I’m also working in ML. Here’s a great resource: https://madewithml.com. Also, check out Noah Gift’s book Practical MLOPs.
- Ask HN: Resource to learn how to train and use ML Models
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Need help to find resources to learn ml ops
Try replicating this setup: https://madewithml.com/
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MLops Resources
madewithml
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Ask HN: How do I get started with MLOps?
There's a really nice website by Goku Mohandas called Made With ML. IMO it is the best practical guide to MLOps out there: https://madewithml.com
Incase you want to dive a little deeper, https://fullstackdeeplearning.com/course/2022/ is also something I have been recommended by folks.
- Resources for Current DE Interested in Learning Data Science
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Do organizations still need machine learning engineers?
madewithml is pretty sweet, especially the MLOps side of things. It'll give you good skills in how development in Python and deploying ML works.
What are some alternatives?
RL-Adventure - Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
flux-beamer - Flux is a modern style beamer presentation.
mlops-zoomcamp - Free MLOps course from DataTalks.Club
DeepReinforcementLearningInAction - Code from the Deep Reinforcement Learning in Action book from Manning, Inc
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
implementation-matters
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
Copulas - A library to model multivariate data using copulas.
ETCI-2021-Competition-on-Flood-Detection - Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training
awesome-mlops - A curated list of references for MLOps