practical-mlops-book
[Book-2021] Practical MLOps O'Reilly Book (by paiml)
Deep-Learning-In-Production
Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples. (by The-AI-Summer)
| practical-mlops-book | Deep-Learning-In-Production | |
|---|---|---|
| 1 | 2 | |
| 652 | 1,073 | |
| 6.1% | 0.8% | |
| 0.0 | 0.0 | |
| almost 2 years ago | about 1 year ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | - |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
practical-mlops-book
Posts with mentions or reviews of practical-mlops-book.
We have used some of these posts to build our list of alternatives
and similar projects.
Deep-Learning-In-Production
Posts with mentions or reviews of Deep-Learning-In-Production.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[P] Deep Learning in Production Book
The book is based on an old articles series we wrote on our blog so a big portion of the content is already available for free. We just organized/restructured some of the articles and we added some new material. We use a variety of examples with libraries such as Tensorflow, Flask, uWSGI, Nginx, Docker, Kubernetes, Tensorflow Extended, Google Cloud, Vertex AI. The full code and the articles can be found on Github (https://github.com/The-AI-Summer/Deep-Learning-In-Production)
- [D] Deep learning in Production
What are some alternatives?
When comparing practical-mlops-book and Deep-Learning-In-Production you can also consider the following projects:
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.
strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath