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Leaf
Leaf

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TensorFlow
TensorFlow

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Leaf vs TensorFlow: What are the differences?

Developers describe Leaf as "Machine learning framework in Rust". Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack. On the other hand, TensorFlow is detailed as "Open Source Software Library for Machine Intelligence". TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

Leaf and TensorFlow belong to "Machine Learning Tools" category of the tech stack.

Leaf is an open source tool with 5.4K GitHub stars and 269 GitHub forks. Here's a link to Leaf's open source repository on GitHub.

What is Leaf?

Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.

What is TensorFlow?

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
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      What are some alternatives to Leaf and TensorFlow?
      scikit-learn
      scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      PyTorch
      PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
      ML Kit
      ML Kit brings Google’s machine learning expertise to mobile developers in a powerful and easy-to-use package.
      CUDA
      A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
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      Avatar of Eliana Abraham
      Eliana Abraham uses TensorFlowTensorFlow

      Machine Learning in EECS 445

      Avatar of Taylor Host
      Taylor Host uses TensorFlowTensorFlow

      Pilot integration for retraining.

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