It's possible to create neural networks from raw code. But there are many code libraries you can use to speed up the process. These libraries include Microsoft CNTK, Google TensorFlow, Theano, PyTorch ...

What are some important engineering and design decisions you made in creating Keras? originally appeared on Quora - the knowledge sharing network where compelling questions are answered by people with ...

If you’re a data scientist who has been wanting to break into the deep learning realm, here is a great learning resource that can guide you through this journey. It’s pretty much an all-inclusive ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Google open source machine learning library TensorFlow 2.0 is now ...

As I discussed in my review of PyTorch, the foundational deep neural network (DNN) frameworks such as TensorFlow (Google) and CNTK (Microsoft) tend to be hard to use for model building. However, ...

The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in ...

Google LLC today announced a new tool called TensorFlow Lite Model Maker, which uses a technique known as transfer learning to adapt machine learning models to custom data sets. TensorFlow Lite is a ...

At version r1.5, Google's open source machine learning and neural network library is more capable, more mature, and easier to learn and use If you looked at TensorFlow as a deep learning framework ...