django-celery
Keras
django-celery | Keras | |
---|---|---|
3 | 78 | |
1,514 | 60,972 | |
0.0% | 0.3% | |
0.0 | 9.9 | |
over 1 year ago | 4 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
django-celery
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3% of 666 Python codebases we checked had a silently failing unit test
https://github.com/ansible-community/ara/pull/358 https://github.com/b12io/orchestra/pull/830 https://github.com/batiste/django-page-cms/pull/210 https://github.com/carpentries/amy/pull/2130 https://github.com/celery/django-celery/pull/612 https://github.com/django-cms/django-cms/pull/7241 https://github.com/django-oscar/django-oscar/pull/3867 https://github.com/esrg-knights/Squire/pull/253https://github.com/Frojd/django-react-templatetags/pull/64 https://github.com/groveco/django-sql-explorer/pull/474 https://github.com/jazzband/django-silk/pull/550 https://github.com/keras-team/keras/pull/16073 https://github.com/ministryofjustice/cla_backend/pull/773 https://github.com/nitely/Spirit/pull/306 https://github.com/python/pythondotorg/pull/1987 https://github.com/rapidpro/rapidpro/pull/1610 https://github.com/ray-project/ray/pull/22396 https://github.com/saltstack/salt/pull/61647 https://github.com/Swiss-Polar-Institute/project-application/pull/483 https://github.com/UEWBot/dipvis/pull/216
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Database character sets and collations explained – why utf8 is not UTF-8
> they would now need to store max 4N bytes, which (with a high N) can exceed internal limits such as maximum length of an index key.
Specifically, indexes are limited to 767 bytes (some say 768?), which means 191 utf8mb4 characters. So your otherwise-innocuous VARCHAR(255) primary key breaks. I’ve seen this multiple times, e.g. django-celery probably still has this: https://github.com/celery/django-celery/issues/259.
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Django API Text Processing?!?
For small projects you'll be fine just doing it in the view. For bigger projects you would want to use a task scheduler like Celery and with django-celery to distribute the workload in the background.
Keras
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Library for Machine learning and quantum computing
Keras
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My Favorite DevTools to Build AI/ML Applications!
As a beginner, I was looking for something simple and flexible for developing deep learning models and that is when I found Keras. Many AI/ML professionals appreciate Keras for its simplicity and efficiency in prototyping and developing deep learning models, making it a preferred choice, especially for beginners and for projects requiring rapid development.
- Release: Keras 3.3.0
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Getting Started with Gemma Models
After setting the variables for the environment, the next step is to install dependencies. To use Gemma, KerasNLP is the dependency used. KerasNLP is a collection of natural language processing (NLP) models implemented in Keras and runnable on JAX, PyTorch, and TensorFlow.
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Keras 3.0
All breaking changes are listed here: https://github.com/keras-team/keras/issues/18467
You can use this migration guide to identify and fix each of these issues (and further, making your code run on JAX or PyTorch): https://keras.io/guides/migrating_to_keras_3/
- Keras 3: A new multi-back end Keras
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Can someone explain how keras code gets into the Tensorflow package?
I'm guessing the "real" keras code is coming from the keras repository. Is that a correct assumption? How does that version of Keras get there? If I wanted to write my own activation layer next to ELU, where exactly would I do that?
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How popular are libraries in each technology
Other popular machine learning tools include PyTorch, Keras, and Scikit-learn. PyTorch is an open-source machine learning library developed by Facebook that is known for its ease of use and flexibility. Keras is a high-level neural networks API that is written in Python and is known for its simplicity. Scikit-learn is a machine learning library for Python that is used for data analysis and data mining tasks.
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List of AI-Models
Click to Learn more...
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Official Question Thread! Ask /r/photography anything you want to know about photography or cameras! Don't be shy! Newbies welcome!
I'm not aware of anything off-the-shelf, but if you have sufficient programming experience, one way to do this would be to build a large dataset of reference images and pictures and use something like keras to train a convolutional neural network on them.
What are some alternatives?
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.
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
celery-progress - Drop in, configurable, dependency-free progress bars for your Django/Celery applications.
scikit-learn - scikit-learn: machine learning in Python
jasmin - Jasmin - Open source SMS gateway
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
django-silk - Silky smooth profiling for Django
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
flower - Real-time monitor and web admin for Celery distributed task queue
tensorflow - An Open Source Machine Learning Framework for Everyone
django-cms - The easy-to-use and developer-friendly enterprise CMS powered by Django
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.