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Recent & Upcoming Talks
2019
Challenges for Machine Learning Systems toward Continuous Improvement
When executing machine learning pipelines for trainings and inferences, the systems and machine learning infrastructures vary depending …
2019-11-22 14:20 — 15:00
Winc Aichi, Nagoya
Aki Ariga
Slides
How do you debug/test your Workflow?
Developping and testing for workflows productively is hard. In this session, I talk about how to develop heavy data dependent workflow …
2019-08-30 —
Shinjuku, Tokyo
Aki Ariga
Slides
2018
Managing Machine Learning workflows on Treasure Data
2018-10-17 —
Shibuya, Japan
Aki Ariga
Slides
仕事ではじめる機械学習
2018-05-17 —
Tokyo, Japan
Aki Ariga
Slides
2017
Train, predict, and serve: How to put your machine learning model into production
Adopting a machine learning system is an essential step for enterprise companies to progress to the next stage of their business. …
2017-12-06 13:45 — 14:25
Suntec Singapore Convention & Exhibition Centre, Singapore
Aki Ariga
Slides
機械学習システムのデプロイパターン
2017-11-07 —
Tokyo, Japan
Aki Ariga
Slides
Invited talk: データサイエンティストからみた統合されたデータ分析基盤の恩恵
In this session, we will introduce the benefits of the integrated data analysis platform, which is important for using data in the …
2017-06-27 14:00 — 14:25
Tokyo, Japan
Cloudera Data Science WorkbenchとPySparkを使って好きなPythonライブラリを分散で使う
An introduction of using artibary Python packages on PySpark with Cloudera Data Science Workbench
2017-06-02 19:30 — 20:00
Shibuya, Japan
Slides
A data enginnering and data science platform based on Hadoop/Spark
Using Cloudera Enterprise, it is possible to build and operate an enterprise-grade Hadoop/Spark platform. To make use of big data, what …
2017-02-07 13:20 — 13:55
Tokyo, Japan
Slides
Video
2016
大規模データに対するデータサイエンスの進め方
2016-11-08 —
Tokyo, Japan
Slides
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