A collection of all country flags in SVG — plus the CSS for easier integration.
Source: flag-icon-css
Train Your Brain to Focus
Next time you are sitting in a meeting, take a look around. The odds are high that you will see your colleagues checking screens, texting, and emailing while someone is talking or making a presentation. Many of us are proud of our prowess in multitasking, and wear it like a badge of honor. Multitasking may […]
Source: Train Your Brain to Focus
Neural Networks and Deep Learning (Online book)
Neural Networks and Deep Learning is a free online book. The book will teach you about:
- Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data
- Deep learning, a powerful set of techniques for learning in neural networks
http://neuralnetworksanddeeplearning.com/index.html
JavaScript 30 — Build 30 things with vanilla JS in 30 days with 30 tutorials
Build 30 things with vanilla JS in 30 days with 30 tutorials
Source: JavaScript 30 — Build 30 things with vanilla JS in 30 days with 30 tutorials
Infographic klimaatagenda / Ministerie van Infrastructuur en Milieu
Het klimaat verandert. De gemiddelde temperatuur stijgt, in Nederland nog sneller dan elders in de wereld. Hoe werkt klimaatverandering en wat betekent dit concreet voor ons? Hoe kunnen we extreme klimaatverandering voorkomen en ons tegelijk aanpassen aan onvermijdelijke gevolgen?
Source: Infographic klimaatagenda / Ministerie van Infrastructuur en Milieu
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 GitXiv website is open-source.
- For ideas/bugs/feature requests, open a Issue.
- Collaborate & discuss on the Wiki.
- GitXiv has a RSS feed, a Twitter and GitHub Account.
- GitXiv was created by Samim & maintained with Graphific.
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