TensorFlow was originally a deep learning research project of the Google Brain Team that has since become–by way of collaboration with 50 teams at Google–an open source library deployed across ...

Applying machine learning algorithms and libraries: Standard implementations of machine learning algorithms are available through libraries, packages, and APIs (such as scikit-learn, Theano, Spark ...

TensorFlow 2.0, released in October 2019, revamped the framework significantly based on user feedback. The result is a machine learning framework that is easier to work with—for example, by ...

Cheat Sheet: 5 Things Everyone Should Know About Machine Learning. ... A machine learning algorithm is given a “teaching set” of data, then asked to use that data to answer a question.

TensorFlow has become the most popular tool and framework for machine learning in a short span of time. It enjoys tremendous popularity among ML engineers and developers. According to the Hacker ...

The Machine Learning Algorithm Cheat Sheet is a good place to start when picking a model. Check out this article to understand how best to use the cheat sheet.

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 ...

At the heart of this transformation is TensorFlow, Google's open-source platform that has become synonymous with machine learning. This article explores TensorFlow's capabilities within the robust and ...

Google's TensorFlow team released TensorFlow Lattice today to help developers ensure that their machine learning models adhere to global trends even when training data is noisy. Lattice draws from ...

Google (the real Google, within Alphabet) has announced a new, open-source machine learning platform called TensorFlow (Opens in a new window), one which could greatly accelerate the pace at which ...