Keras
Pytorch
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Keras | Pytorch | |
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74 | 328 | |
60,643 | 76,684 | |
0.7% | 1.9% | |
9.9 | 10.0 | |
4 days ago | about 4 hours ago | |
Python | Python | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
Keras
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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/
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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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I got advice on building ai apps.
Keras documentation: https://keras.io/
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
3. Keras Keras is a high-level neural networks API written in Python that’s built on top of TensorFlow. It’s designed to enable fast experimentation with deep learning, allowing you to build and train models with just a few lines of code. If you’re new to deep learning or just want a more user-friendly interface, Keras is the way to go.
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How to query pandas DataFrames with SQL
Pandas comes with many complex tabular data operations. And, since it exists in a Python environment, it can be coupled with lots of other powerful libraries, such as Requests (for connecting to other APIs), Matplotlib (for plotting data), Keras (for training machine learning models), and many more.
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The Essentials of a Contributor-friendly Open-source Project
Our trick is to support GitHub Codespaces, which provides a web-based Visual Studio Code IDE. The best thing is you can specify a Dockerfile with all the required dependency software installed. With one click on the repo’s webpage, your contributors are ready to code. Here is our setup for your reference.
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DO YOU YAML?
If you’re looking for further resources on running TensorFlow and Keras on a newer MacBook, I recommend checking out this YouTube video: How to Install Keras GPU for Mac M1/M2 with Conda
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Doing k-fold analysis
The thing that pops right into my mind is the following issue: https://github.com/keras-team/keras/issues/13118 People are still reporting memory leaks when calling model.predict and I wouldn't be surprised if model.fit also leaked when called multiple times. Maybe this is a good starting point for your investigation. If this is unrelated, I'm sorry in forward.
Pytorch
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Best AI Tools for Students Learning Development and Engineering
Which label applies to a tool sometimes depends on what you do with it. For example, PyTorch or TensorFlow can be called a library, a toolkit, or a machine-learning framework.
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Element-wise vs Matrix vs Dot multiplication
In PyTorch with * or mul(). ` or mul()` can multiply 0D or more D tensors by element-wise multiplication:
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Bash Debugging
When I was at Facebook, I wrote a Python script to extract shell scripts from GitHub Actions workflows, so we could run them all through ShellCheck: https://github.com/pytorch/pytorch/blob/69e0bda9996865e319db...
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Releasing The Force Of Machine Learning: A Novice’s Guide 😃
PyTorch: An open-source deep learning framework that facilitates dynamic computational graphs, making it flexible and efficient for research and production.
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How To Implement Data Streaming In PyTorch From A Remote Database
In this blog post, we will go through a full example and setup a data stream to PyTorch from a playground dataset on a remote database.
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Introducing Flama for Robust Machine Learning APIs
PyTorch
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Beyond Backpropagation - Higher Order, Forward and Reverse-mode Automatic Differentiation for Tensorken
This post describes how I added automatic differentiation to Tensorken. Tensorken is my attempt to build a fully featured yet easy-to-understand and hackable implementation of a deep learning library in Rust. It takes inspiration from the likes of PyTorch, Tinygrad, and JAX.
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Apple releases MLX for Apple Silicon
The design of MLX is inspired by frameworks like NumPy, PyTorch, Jax, and ArrayFire.
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MLX: An array framework for Apple Silicon
Exactly right that this targets a narrower surface to enable many deep learning models. I wonder how uncommon it is to hit some operation that is not included, though? It seems pretty common from a PyTorch MPS tracking issue:
https://github.com/pytorch/pytorch/issues/77764
NVIDIA's moat is not just in providing BLAS++ operations, but extending this to a wider range of cuSPARSE, cuSOLVE, cuTENSOR, etc. Without these, it feels like Apple is just trying to play catch up with whatever is popular and unsupported...
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🔥🚀 Top 10 Open-Source Must-Have Tools for Crafting Your Own Chatbot 🤖💬
#3 PyTorch
What are some alternatives?
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
scikit-learn - scikit-learn: machine learning in Python
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
flax - Flax is a neural network library for JAX that is designed for flexibility.
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
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
Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java
tensorflow - An Open Source Machine Learning Framework for Everyone
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.