PaddlePaddle
Keras
| PaddlePaddle | Keras | |
|---|---|---|
| 7 | 83 | |
| 22,298 | 62,139 | |
| 0.3% | 0.3% | |
| 10.0 | 9.9 | |
| 5 days ago | 5 days ago | |
| C++ | Python | |
| Apache License 2.0 | 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.
PaddlePaddle
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Fixing bugs in your AI: let's analyze bugs in OpenVINO
It's hard to define what exactly the correct code should look like in this case. However, let's take a guess. The code is in the OpenVINO Paddle Frontend module, which parses the model generated by the PaddlePaddle framework. If we search for the 'pad3d' name in the project, we can find the following description:
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List of AI-Models
Click to Learn more...
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Ask HN: Are there any notable Chinese FLOSS projects?
PaddlePaddle?
https://github.com/PaddlePaddle/Paddle
Also, Baidu have quite a few OSS projects out there in general.
https://github.com/baidu
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Volcano vs Yunikorn vs Knative
Volcano is a batch scheduler on top of Kube-batch targetting spark-operator, plain old MPI, chinesium paddlepaddle, and Kromwell HPC.
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Baidu AI Researchers Introduce SE-MoE That Proposes Elastic MoE Training With 2D Prefetch And Fusion Communication Over Hierarchical Storage
Continue reading | Check out the paper, and Github
- I have issue with only __habs for half datatype? Please help!
- Alternatives to google collab?
Keras
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Top 8 OpenSource Tools for AI Startups
Star on GitHub ⭐ - Keras
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Top 5 Production-Ready Open Source AI Libraries for Engineering Teams
At its heart is TensorFlow Core, which provides low-level APIs for building custom models and performing computations using tensors (multi-dimensional arrays). It has a high-level API, Keras, which simplifies the process of building machine learning models. It also has a large community, where you can share ideas, contribute, and get help if you are stuck.
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Las 10 Mejores Herramientas de Inteligencia Artificial de Código Abierto
(https://dev-to-uploads.s3.amazonaws.com/uploads/articles/92cup4lywcjfq83xg0ea.png)
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Using Google Magika to build an AI-powered file type detector
The core model architecture for Magika was implemented using Keras, a popular open source deep learning framework that enables Google researchers to experiment quickly with new models.
- Side Quest #3: maybe the real Deepfakes were the friends we made along the way
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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/
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
PyTorch-NLP - Basic Utilities for PyTorch Natural Language Processing (NLP)
scikit-learn - scikit-learn: machine learning in Python
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
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
MLflow - Open source platform for the machine learning lifecycle
python-recsys - A python library for implementing a recommender system
gym - A toolkit for developing and comparing reinforcement learning algorithms.
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.