This is the Thoth Station
Using artificial intelligence to analyse and recommend software stacks for artificial intelligence applications.
AI on any device. Hundreds of Deep Learning Models Tuned for Popular Use Cases and Devices. An easy guide for anyone who wants to learn the Xnor SDK.
OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi – PyImageSearch
Inside this tutorial we will learn how to utilize the OpenVINO toolkit with OpenCV for faster deep learning inference on the Raspberry Pi.
OpenVINO, OpenCV, and Movidius NCS on the Raspberry Pi
An interactive game driven by the brain and muscle tracking EEG data with OpenBCI sensors.
Game interaction with their body movement tracked by OpenBCI muscle sensing board
MLK is a knowledge sharing community platform for machine learning enthusiasts, beginners and experts. Let us create a powerful hub together to Make AI Simple for everyone.
MLK – Machine Learning Knowledge
A free online introduction to artificial intelligence for non-experts
Learn more about Reaktor’s and the University of Helsinki’s AI course – no programming or complicated math required.
Elements of AI
An AI education platform for building games, programming robots & training AI models
Fryden Learning Machines is the home of the Fryden computer and the Be the Machine role playing game. There are also lessons and information about Machine Learning that are designed for middle school STEM students building a Fryden computer, but are suitable for anyone trying to understand the subject.
Fryden Learning Machine
Brainwave Adaptive Learning™ enabled with an EEG headband and the Brainiak™ Analytics AI software app is an effective solution for you to provide a truly adaptive learning experience to your students in class room as well as online.
Brainwave – intellADAPT
Building Your First ConvNet
This post is to help you get up to speed on training ConvNet models in the cloud without the hassles of setting up a VM, AWS instance, or anything of that sort. You’ll be able to design your own classification task with lots of images and train your own ConvNet models.