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 ...

You can use existing models, convert Python TensorFlow models, use transfer learning to retrain existing models with your own data, and develop models from scratch.

TensorFlow is a Python-friendly open source library for developing machine learning applications and neural networks. Here's what you need to know about TensorFlow.

I strongly recommend using the Anaconda distribution of Python, which has all the packages you need to run Keras with TensorFlow. In this article I address installation on a Windows 10 machine.

It also makes extensive use of Python scripts, but if you’re comfortable with that and you have an application for computer vision, [Evan]’s tutorial will get you started.

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. This TensorFlow guide covers why the library matters, how to use it and more.

When the time comes to add an object recognizer to your hack, all you need do is choose from many of the available ones and retrain it for your particular objects of interest. To help with that, [E… ...

Programming languages: Python developers reveal what they use it for and their top tools New global survey shows that Python developers love machine learning, but just don't call them data scientists.

Despite some of the inherent complexities of using FPGAs for implementing deep neural networks, there is a strong efficiency case for using reprogrammable devices for both training and inference.