Quantum Computing Programming for Primitive Problems (Run Quantum Algorithm)

In order to solve the real problem with quantum computing, it’s also important to understand algorithms as well as quantum logic gates.
Here I show primitive programming sample to solve some problem for your very beginning and introductions.


MXNet Distributed Training with Azure ML service (Custom Configuration for Training)

In this post, I proceed to more advanced topics by showing you how to set up (customize) your Azure Machine Learning Compute (AmlCompute) for the practical training. In the last part of this post, I’ll show you Apache MXNet distributed training example with Azure Machine Learning service.

Run Your FPGA Accelerated Inference (the basis of “Project Brainwave”)

Project Brainwave provides hardware accelerated machine learning with FPGA.
In Github tutorial, there are several useful helper classes and functions (with python) which encapsulate boilerplate code to achieve provisioning steps. In this post I show you the same steps without these helpers. With these steps I hope it helps you to understand new FPGA-enabled services and how it’s working.