With the help of Python and the NumPy add-on package, I'll explain how to implement back-propagation training using momentum. Neural network momentum is a simple technique that often improves both ...

You don't have to resort to writing C++ to work with popular machine learning libraries such as Microsoft's CNTK and Google's TensorFlow. Instead, we'll use some Python and NumPy to tackle the task of ...

While deep neural networks are all the rage, the complexity of the major frameworks has been a barrier to their use for developers new to machine learning. There have been several proposals for ...

We will create a Deep Neural Network python from scratch. We are not going to use Tensorflow or any built-in model to write the code, but it's entirely from scratch in python. We will code Deep Neural ...

Neural networks are all the rage right now with increasing numbers of hackers, students, researchers, and businesses getting involved. The last resurgence was in the 80s and 90s, when there was little ...

As a fun project I thought I’d put Google’s Inception-v3 neural network on a Raspberry Pi to see how well it does at recognizing objects first hand. It turned out to be not only fun to implement, but ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. This article dives into the happens-before ...

Artificial digital neural network concept. Neural network software enables the implementation, deployment and training of artificial neural networks. These networks are designed to mimic the behavior ...

Google used TensorFlow to build its Magenta project, which aims to advance machine generated art, and recently released a 90-second piano melody created solely by a neural network. This gives an idea ...