Based on our record, Luigi should be more popular than Deeplearning4j. It has been mentiond 9 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 9 months ago
Maybe if your use case is “smallish” and doesn’t require the whole studio suite you could check out apscheduler for doing python “tasks” on a schedule and luigi to build pipelines. Source: almost 2 years ago
What are you trying to do? Distributed scheduler with a single instance? No database? Are you sure you don't just mean "a scheduler" ala Luigi? https://github.com/spotify/luigi. - Source: Hacker News / about 2 years ago
It's good to know what Airflow is not the only one on the market. There are Dagster and Spotify Luigi and others. But they have different pros and cons, be sure that you did a good investigation on the market to choose the best suitable tool for your tasks. - Source: dev.to / over 2 years ago
MLOps is a HUGE area to explore, and not surprisingly, there are many startups showing up in this space. If you want to get it on the latest trends, then I would look at workflow orchestration frameworks such as Metaflow (started off at Netflix, is now spinning off into its own enterprise business, https://metaflow.org/), Kubeflow (used at Google, https://www.kubeflow.org/), Airflow (used at Airbnb,... Source: over 2 years ago
While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features. Source: almost 3 years ago
Would recommend taking a look at dl4j: https://deeplearning4j.org. Source: about 3 years ago
We use DeepLearning4j in this chapter because it is written in Java and easy to use with Clojure. In a later chapter we will use the Clojure library libpython-clj to access other deep learning-based tools like the Hugging Face Transformer models for question answering systems as well as the spaCy Python library for NLP. Source: about 3 years ago
FastAPI. Or even simpler: DL4J, to be used in Java when we need to communicate with the rest of the applications in real time. Source: about 3 years ago
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...