Showing posts with label embedded. Show all posts
Showing posts with label embedded. Show all posts

Tuesday, April 14, 2020

[Links of the Day] 14/04/2020 : Time series dynamical attractors Autoencoder , Binarized Neural Network framework, Machine learning and Databases

  • Deep learning of dynamical attractors from time series measurements : the authors propose a general embedding technique for time series, consisting of an autoencoder trained with a novel latent-space loss function. Worth giving it a look if you deal with time series.
  • larq : open-source Python library for training neural networks with extremely low-precision weights and activations, such as Binarized Neural Networks. Basically, this framework is aiming at embedded / FPGA / ASIC machine learning models deployment. A fantastic resource and great model zoo on top of that.
  • Cloudy with a chance of DBMS : Databases are going to embedded more and more machine learning solution. Big query from Google already does that. But it's just a question of time for most mainstream DB to offer ML service.

Tuesday, March 03, 2020

[Links of the Day] 03/03/2020 : Embedded linux build toolchain, Cyber security body of knowledge, AWS API change tracker

  • BuildRoot : a tool to generate embedded Linux systems through cross-compilation.
  • Cybok v1.0 : aims to codify the foundational and generally recognised knowledge on cyber security. In the same fashion as SWEBOK, CyBOK is meant to be a guide to the body of knowledge; the knowledge that it codifies already exists in literature such as textbooks, academic research articles, technical reports, white papers, and standards. [website]
  • AWS API Change : feel overwhelmed by the pass of change of the AWS API stack. Have no idea why your code doesn't work anymore? Want to use the latest, shiniest aws feature. You need this, this web page tracks all the API change in AWS stack.