It is a modular and extensible codebase including data pipeline, and popular SSL algorithms for standardization of SSL ablations. Meanwhile, pre-trained versions of the state-of-the-art neural models for CV tasks are provided. It is easy-to-use/extend, affordable, and comprehensive for developing and evaluating SSL algorithms.
USB is a tool in the Development & Training Tools category of a tech stack.
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What are some alternatives to USB?
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.
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.
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
PyTorch, Python are some of the popular tools that integrate with USB. Here's a list of all 2 tools that integrate with USB.