Pipe T5QC TensorFlow - A New Machine Learning System Released as Open-Source Software by Google

TensorFlow - A New Machine Learning System Released as Open-Source Software by Google

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in google on (#T5QC)
On Monday, Google announced the release, as an opensource project (Apache License), of TensorFlow.

According to Google, TensorFlow is their next-gen machine learning system, fixing the shortcomings of DistBelief, the AI system behind several of Google tools such as speech recognition on Android (think "OK Google"), description-based image search in Google Photos or even automatic email reply suggestions.

From the official announcement:
TensorFlow has extensive built-in support for deep learning, but is far more general than that -- any computation that you can express as a computational flow graph, you can compute with TensorFlow (see some examples). Any gradient-based machine learning algorithm will benefit from TensorFlow’s auto-differentiation and suite of first-rate optimizers. And it’s easy to express your new ideas in TensorFlow via the flexible Python interface.
note: "Deep Learning" is what used to be called "Artificial Neural Networks", but on steroids.

More technical explanations are available in their whitepaper and code is on GitHub.

History


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2015-11-16 04:07
TensorFlow - A New Machine Learning System Released as Open-Source Software by Google
bryan@pipedot.org
On Monday, Google announced the release, as an opensource project (Apache License), of TensorFlow.

According to Google, TensorFlow is their next-gen machine learning system, fixing the shortcomings of DistBelief, the AI system behind several of Google tools such as speech recognition on Android (think "OK Google"), description-based image search in Google Photos or even automatic email reply suggestions.

From the official announcement:
TensorFlow has extensive built-in support for deep learning, but is far more general than that -- any computation that you can express as a computational flow graph, you can compute with TensorFlow (see some examples). Any gradient-based machine learning algorithm will benefit from TensorFlow’'s auto-differentiation and suite of first-rate optimizers. And it’'s easy to express your new ideas in TensorFlow via the flexible Python interface.
note: "Deep Learning" is what used to be called "Artificial Neural Networks", but on steroids.

More technical explanations are available in their whitepaper and code is on GitHub.
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