machine_learning_examples
neptune-contrib
Our great sponsors
| machine_learning_examples | neptune-contrib | |
|---|---|---|
| 3 | - | |
| 8,091 | 27 | |
| - | - | |
| 5.3 | 0.0 | |
| 8 days ago | over 1 year ago | |
| Python | Python | |
| - | MIT License |
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.
machine_learning_examples
-
Doubt about numpy's eigen calculation
Does that mean that the example I found on the internet is wrong (I think it comes from a DL Course, so I'd imagine it is not wrong)? or does it mean that I am comparing two different things? I guess this has to deal with right and left eigen vectors as u/JanneJM pointed out in her comment?
-
How to save an attention model for deployment/exposing to an API?
I've been following a course teaching how to make an attention model for neural machine translation, This is the file inside the repo. I know that I'll have to use certain functions to make the textual input be processed in encodings and tokens, but those functions use certain instances of the model, which I don't know if I should keep or not. If anyone can please take a look and help me out here, it'd be really really appreciated.
neptune-contrib
We haven't tracked posts mentioning neptune-contrib yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
scikit-learn - scikit-learn: machine learning in Python
applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Keras - Deep Learning for humans
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
tensorflow - An Open Source Machine Learning Framework for Everyone
neptune-client - 📘 The MLOps stack component for experiment tracking
bodywork - ML pipeline orchestration and model deployments on Kubernetes.
polyaxon - MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
TFLearn - Deep learning library featuring a higher-level API for TensorFlow.