machine_learning

The first conference of Operational Machine Learning: OpML ‘19

I attended OpML ’19 is a conference for “Operational Machine Learning” held at Santa Clara on May 20th. OpML ‘19 _The 2019 USENIX Conference on Operational Machine Learning (OpML ‘19) will take place on Monday, May 20, 2019, at the…_www.usenix.org[](https://www.usenix.org/conference/opml19) The scope of this conference is varied and seems not to be specified yet, even if I attended it. I’ll borrow the description from the OpML website. The 2019 USENIX Conference on Operational Machine Learning (OpML ’19) provides a forum for both researchers and industry practitioners to develop and bring impactful research advances and cutting edge solutions to the pervasive challenges of ML production lifecycle management.

Ruby for Data Science and Machine Learning

I attended RubyKaigi 2019 held at Fukuoka from Apr 18 to Apr 21. This year’s RubyKaigi was a really great opportunity for me to know the possibility of Data Science and Machine Learning for Ruby. Data Science and Ruby As many of you may know, Ruby is widely known for web application with such as Ruby on Rails, but there is another momentum of Ruby or non-Python language. Here is the list of the sessions about Data Science.

Why OSS based machine learning is good?

This article is translation of Japanese version. After releasing of TensorFlow, the movement of OSS-based machine learning is accelerating. François Chollet, the creator of Keras, says the essential point of this change. I think his phrase is enough, but in this article, I would like to organize why open source machine learning is great, and what recent trends are. tl;dr Machine learning and deep learning frameworks have become standard things for software engineers Since arXiv becomes very famous, many papers are published before peer review of international conferences.