If you actually need a deep learning model, PyTorch and TensorFlow are both good choices ...

Researchers at North Carolina State University recently presented a paper at the International Conference on Supercomputing (ICS) on their new technique, "deep reuse" (DR), that can speed up ...

When deploying large-scale deep learning applications, C++ may be a better choice than Python to meet application demands or to optimize model performance. Therefore, I specifically document my recent ...

Abstract We introduce Bayesian code diffusion, a new deep learning program optimization strategy devised to accelerate the auto-tuning process of deep ...

Google last week open sourced TensorFlow, a new machine learning library used in deep learning projects. Even though the Web giant has just started using the software in its products, it apparently ...

A key part of the TensorFlow ecosystem is the Keras API suite, which provides a set of Python language-based deep learning capabilities on top of the core TensorFlow technology.

TensorFlow seems to perform as well as anything out there for neural network and deep learning training, despite an early benchmark that falsely indicated otherwise because of differing GPU libraries.

TensorFlow isn’t alone in the deep learning field; in fact, there are a number of other companies with machine learning frameworks, including the following. Theano Torch Caffe neon H2O.ai ...

Google announced yesterday that its Deep Learning algorithm, TensorFlow, has been open-sourced. According to Google, this is the second generation machine learning algorithm, with the first one ...

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 ...