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GE Healthcare used TensorFlow to increase the speed and accuracy of MRIs in identifying specific body parts. [74] Google used TensorFlow to create DermAssist, a free mobile application that allows users to take pictures of their skin and identify potential health complications. [75]
Design goal Compatible with other formats Self-contained DNN Model Pre-processing and Post-processing Run-time configuration for tuning & calibration DNN model interconnect Common platform TensorFlow, Keras, Caffe, Torch: Algorithm training No No / Separate files in most formats No No No Yes ONNX: Algorithm training Yes
Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with ...
Add & manage files; light & dark themes; create/follow embedded tutorials; responsive design testing mode Webpaw [aa] Free Yes Yes Yes Yes Yes Less, TypeScript, development assets, import from HTML/GitHub, social login, multiple layouts Liveweave [ab] Free Yes Yes Yes Yes No Plunker [ac] Free Yes Yes Yes Yes No
One prominent example is molecular drug design. [6] [7] [8] Each input sample is a graph representation of a molecule, where atoms form the nodes and chemical bonds between atoms form the edges. In addition to the graph representation, the input also includes known chemical properties for each of the atoms.
The company's (now discontinued) open-source deep learning framework is called neon. [5] Neon – which the company said would outperform rival frameworks such as Caffe, Theano, Torch, and TensorFlow [5] – would achieve its performance advantage through assembler-level optimization, multi-GPU support, and use of an algorithm called Winograd for computing convolutions, which are common ...
Design [ edit ] "Tensor" is a reference to Google's TensorFlow and Tensor Processing Unit technologies, and the chip is developed by the Google Silicon team housed within the company's hardware division , led by vice president and general manager Phil Carmack alongside senior director Monika Gupta, [ 15 ] in conjunction with the Google Research ...
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.