open source tools for Deep Learning

Source: The major advancements in Deep Learning in 2016 – Tryolabs Blog

Open source tools are everywhere (as we highlighted in our 10 main takeaways from MLconf SF blogpost). They are used and created by researchers and companies. Here is a list of the most popular tools in 2016 for Deep Learning:

  • TensorFlow by Google.
  • Keras by François Chollet.
  • CNTK by Microsoft.
  • MXNET by Distributed (Deep) Machine Learning Community. Adapted by Amazon.
  • Theano by Université de Montréal.
  • Torch by Ronan Collobert, Koray Kavukcuoglu, Clement Farabet. Widely used by Facebook.

 

GitXiv: Collaborative Open Computer Science

Source: GitXiv: Collaborative Open Computer Science

In recent years, a highly interesting pattern has emerged: Computer scientists release new research findings on arXiv and just days later, developers release an open-source implementation on GitHub. This pattern is immensely powerful. One could call it collaborative open computer science (cocs).

GitXiv is a space to share collaborative open computer science projects. Countless Github and arXiv links are floating around the web. Its hard to keep track of these gems. GitXiv attempts to solve this problem by offering a collaboratively curated feed of projects. Each project is conveniently presented as arXiv + Github + Links + Discussion. Members can submit their findings and let the community rank and discuss it. A regular newsletter makes it easy to stay up-to-date on recent advancements. It´s free and open. Read more…

 

 

The major advancements in Deep Learning in 2016 – Tryolabs Blog

Deep Learning has been the core topic in the Machine Learning community the last couple of years and 2016 was not the exception. In this article, we will go through the advancements we think have contributed the most (or have the potential) to move the field forward and how organizations and the community are making sure that these powerful technologies are going to be used in a way that is beneficial for all.

Source: The major advancements in Deep Learning in 2016 – Tryolabs Blog