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 ...

A lot of software developers are drawn to Python due to its vast collection of open-source libraries. Lately, there have been a lot of libraries cropping up in the realm of Machine Learning (ML) and ...

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 ...

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, ...

Suppose you have a collection of digital photos you took on a trip to a zoo. You want to programmatically classify each photo as one of the 100 different kinds of animals you photographed: "aardvark," ...

Now more platform than toolkit, TensorFlow has made strides in everything from ease of use to distributed training and deployment The importance of machine learning and deep learning is no longer in ...

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 ...

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 ...

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 News ...