turicreate
Pytorch
| turicreate | Pytorch | |
|---|---|---|
| 2 | 340 | |
| 11,134 | 78,016 | |
| - | 1.4% | |
| 0.0 | 10.0 | |
| 6 months ago | 4 days ago | |
| C++ | Python | |
| BSD 3-clause "New" or "Revised" License | BSD 1-Clause 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.
turicreate
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Mac Studio for Deep Learning
It depends. What kind of ML will you be working with? Apple's neural engine doesn't have an SDK, but they do have https://github.com/apple/turicreate which talks to CoreML. I've been thinking of getting an Mac Studio Ultra and have been researching whether this would be a good investment considering the advances in hardware lately, as well as Apple's release schedule. Been following Tenstorrent for news about their PCIe Gen 4 cards, too. In any case my wallet is going to be hurting soon. Also, have you checked this out? https://machinelearning.apple.com/research/neural-engine-transformers
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I've got a basic prediction model using Random Forest, I'd like to convert it to Core ML model, any idea how I could do this?
What framework/library did you use to create your ML model? There is a very simplified way to create a Random Forest model using Turi create.
Pytorch
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Clasificador de imágenes con una red neuronal convolucional (CNN)
PyTorch (https://pytorch.org/)
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AI enthusiasm #9 - A multilingual chatbot📣🈸
torch is a package to manage tensors and dynamic neural networks in python (GitHub)
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Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
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Library for Machine learning and quantum computing
TensorFlow
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My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
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penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
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Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
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The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
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Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
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Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
DALI - A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
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
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.