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For example, TensorFlow Recommenders and TensorFlow Graphics are libraries for their respective functionalities in recommendation systems and graphics, TensorFlow Federated provides a framework for decentralized data, and TensorFlow Cloud allows users to directly interact with Google Cloud to integrate their local code to Google Cloud. [68]
Manual image annotation is the process of manually defining regions in an image and creating a textual description of those regions. Such annotations can for instance be used to train machine learning algorithms for computer vision applications. This is a list of computer software which can be used for manual annotation of images.
TensorFlow is an open source software library powered by Google Brain that allows anyone to utilize machine learning by providing the tools to train one's own neural network. [2] The tool has been used to develop software using deep learning models that farmers use to reduce the amount of manual labor required to sort their yield, by training ...
If both the "Prior" and "Posterior" cells contain "Manually", the software provides an interface for computing the marginal likelihood and its gradient w.r.t. hyperparameters, which can be feed into an optimization/sampling algorithm, e.g., gradient descent or Markov chain Monte Carlo.
It was eventually refactored into TensorFlow. It was used to train the network in "the cat neuron paper". [12] [14] TensorFlow, an open-source machine-learning software library. He was the primary designers and implementors of the initial system. [15]
MLIR (Multi-Level Intermediate Representation) is a unifying software framework for compiler development. [1] MLIR can make optimal use of a variety of computing platforms such as central processing units (CPUs), graphics processing units (GPUs), data processing units (DPUs), Tensor Processing Units (TPUs), field-programmable gate arrays (FPGAs), artificial intelligence (AI) application ...
AlphaGo Zero's neural network was trained using TensorFlow, with 64 GPU workers and 19 CPU parameter servers. Only four TPUs were used for inference. The neural network initially knew nothing about Go beyond the rules. Unlike earlier versions of AlphaGo, Zero only perceived the board's stones, rather than having some rare human-programmed edge ...
Later, the computation graph becomes a de facto intermediate representation. Standards such as the Open Neural Network Exchange and Neural Network Exchange Format are now widely supported by various deep learning frameworks such as TensorFlow and PyTorch. The idea of service-level composition and serving was investigated in the Zoo subsystem of ...