Приклади вживання Tensorflow Англійська мовою та їх переклад на Українською
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Tensorflow(deep learning).
Google releases TensorFlow 1.0.
TensorFlow Lite for Microcontrollers.
Other highlights from TensorFlow 1.0:.
TensorFlow TensorFlow computations are expressed as stateful dataflow graphs.
Technologies include Python and TensorFlow.
Like TensorFlow and DMTK, it is written in C++, although Python is used to automate and coordinate nodes.
Practical part 2: creating neural network to solve computer vision problem,using tensorflow.
The name TensorFlow derives from the operations that such neural networks perform on multidimensional data arrays, which are referred to as tensors.
However, at the same time the companyhas its own large software project in TensorFlow, as well as its own project Tensor AI Chip.
In May 2019, Google announced that their TensorFlow Lite Micro(also known as TensorFlow Lite for Microcontrollers) and ARM's uTensor would be merging.
It's also why we create everything, including NSynth Super, with open source libraries,including TensorFlow and openFrameworks.
Developed by Google just a few years ago, TensorFlow is an open source software library for numerical computation using data flow graphs.
During the Google I/O Conference in June 2016,Jeff Dean stated that 1,500 repositories on GitHub mentioned TensorFlow, of which only 5 were from Google.
In March 2018, Google announced TensorFlow. js version 1.0 for machine learning in JavaScript and TensorFlow Graphics for deep learning in computer graphics.
Originally developed by researchers andengineers working on the Google Brain team for internal use, TensorFlow was released as an open source project in 2015.
In May 2016, Google announced its Tensor Processing Unit(TPU), an application-specific integrated circuit(a hardware chip)built specifically for machine learning and tailored for TensorFlow.
This specific project is a pilot with the Departmentof Defence, to provide open source TensorFlow APIs that can assist in object recognition on unclassified data," the spokesperson said.
In January 2019, TensorFlow team released a developer preview of the mobile GPU inference engine with OpenGL ES 3.1 Compute Shaders on Android devices and Metal Compute Shaders on iOS devices.
You can download the code freely all over the internet, but it's not easy to set up- you need to configureNvidia's CUDA framework to run the FakeApp TensorFlow code, so the app requires a GeForce GPU.
Edge TPU is Google'spurpose-built ASIC chip designed to run TensorFlow Lite machine learning(ML) models on small client computing devices such as smartphones known as edge computing.
TensorFlow is arguably one of the best deep learning frameworks and has been adopted by several giants such as Airbus, Twitter, IBM, and others mainly due to its highly flexible and modular system architecture.
With its new NeuroPilot, MediaTek is offering a framework that cantranslate code written for other frameworks like TensorFlow, TF Lite, and Caffe 2, theoretically helping development by boosting cross-usage between the various platforms.
When I asked Rajat Monga, who leads the TensorFlow team, about Google's decision he told me,“Having this system open-sourced we're able to collaborate with many other researchers at universities and startups, which gives us new ideas about how we can advance our technology.
Originally designed to help equip Google employees with practical artificial intelligence and machine learning fundamentals,Google rolled out its free TensorFlow workshops in several cities around the world before finally releasing the course to the public.
Google told the Pentagon it could build a system on TensorFlow that would catalog surveillance data, allowing analysts to select a building on a map and get instant access to all relevant surveillance assessments based on computer analysis of drone imagery.
Originally designed to help equip Google employees with practical artificial intelligence and machine learning fundamentals,Google rolled out its free TensorFlow workshops in several cities around the world, finally releasing the course to the public(take it yourself).
While the reference implementation runs on single devices, TensorFlow can run on multiple CPUs and GPUs(with optional CUDA and SYCL extensions for general-purpose computing on graphics processing units).