Essential Cheat Sheets for Machine Learning and Deep Learning Engineers
Learning machine learning and deep learning is difficult for newbies. As well as deep learning libraries are difficult to understand. I am…
Read more »Machine Learning for At-Home Immune Monitoring from Athelas
Athelas is excited to be working with the National Neutropenia Network to bring point-of-care, in-home neutrophil monitoring to the…
Read more »MultiModel: Multi-Task Machine Learning Across Domains
Posted by Łukasz Kaiser, Senior Research Scientist, Google Brain Team and Aidan N. Gomez, Researcher, Department of Computer Science Machine…
Read more »Machine Learning with JavaScript
JAVASCRIPT?! Shouldn’t I be using Python? Am I out of my mind to try those hefty calculations in JavaScript? Am I trying to act cool by using a language that is not Python or R? scikit-learn doesn’t…
Read more »MultiModel: Multi-Task Machine Learning Across Domains
Posted by Łukasz Kaiser, Senior Research Scientist, Google Brain Team and Aidan N. Gomez, Researcher, Department of Computer Science Machine…
Read more »MultiModel: Multi-Task Machine Learning Across Domains
Posted by Łukasz Kaiser, Senior Research Scientist, Google Brain Team and Aidan N. Gomez, Researcher, Department of Computer Science Machine…
Read more »How Lawyers Will Be Killed by the Blockchain and Not Machine Learning
Those which have enjoyed a monopoly for so long due to their protection by Royal Societies and Official registries. Those which require accreditation and continued professional development. I’m not…
Read more »Reproducibility in Machine Learning Workshop (ICML 2017)
Deadline extended to June 22nd! https://sites.google.com/view/icml-reproducibility-workshop/home https://openreview.net/group?id=ICML.cc/2017/RML…
Read more »The world’s first protein database for Machine Learning and AI
Ladies and gentlemen I am incredibly proud and excited to present the very first public product of Peptone, the Database of Structural…
Read more »Stencil Computations for Multi-Core Architectures Based on Machine Learning
Stencil computations are the basis to solve many problems related to Partial Differential Equations (PDEs). Obtaining the best performance with such numerical kernels is a major issue as many critical parameters (architectural features, compiler flags, me…
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