A machine learning workflow with TensorFlow Our architecture consists of training and classification data streamed through Kafka and stored in a persistent, queryable database.

TensorFlow 1.0 not only brings improvements to the framework’s gallery of machine learning functions, but also eases TensorFlow development to Python and Java users and improves debugging.

With this week's release of TensorFlow 1.0, Google has pushed the frontiers of machine learning further in a number of directions. TensorFlow isn't just for neural networks anymore ...

TensorFlow remains the ‘workhouse’ of machine learning at Google In an era where large language models (LLMs) are all the rage, Spinelli emphasized that it’s now even more critical than ever ...

Introduction Machine Learning (ML) stands as one of the most revolutionary technologies of our era, reshaping industries and creating new frontiers in data analysis and automation. At the heart of ...

Google LLC today launched an enterprise version of TensorFlow, the popular open-source artificial intelligence framework it created to run machine learning, deep learning and other statistical and ...

For those unfamiliar, TensorFlow is the company’s open source machine learning software that powers things like Google Translate and many Photos features.

In service of this, the search engine giant has open-sourced “TensorFlow," a scalable machine learning framework that was initially made for internal use in Google’s Machine Intelligence ...

Google today announced the launch of version 0.8 of TensorFlow, its open source library for doing the hard computation work that makes machine learning possible. Normally, a small point update ...

TensorFlow is basically a second-generation machine-learning system, one that Google claims is twice as fast and more flexible, and can be run on an individual smartphone or across data centers ...