👋 Hi, I'm Takuya

Takuya Kitazawa is working on machine learning, data science, and product development at Treasure Data.

I'm passionate about bridging a gap between scientific theory and real-world practice in industry. At Treasure Data, an organization building an enterprise-grade big data analytics platform, I have been practically acted as a data scientist, technical evangelist, sales engineer, product manager, machine learning engineer, and software engineer through the experience of contributing to OSS for scalable ML, building out-of-the-box ML application, presenting at conferences, and working on a variety of customer-facing opportunities.

  k.takuti at gmail.com


  See my resume


Reviewing Ethical Challenges in Recommender Systems
Understanding Array Bisection Algorithm
Hi Product Managers, Are You Creating Products That *You* Love?
Unusual Drinking & Eating Habits: Non-Alcohol, Decaf, Flexitarian
A Journey of Sustainable Development #SDGMOOC


ApacheCon Europe 2019
Apache Hivemall Meets PySpark: Scalable Machine Learning with Hive, Spark, and Python
ApacheCon North America 2019
What's New and Coming to Apache Hivemall: Building More Flexible Machine Learning Solution for Apache Hive and Spark
JuliaCon 2019
Recommendation.jl: Building Recommender Systems in Julia
UMAP 2019
Zero-Coding UMAP in Marketing: A Scalable Platform for Profiling and Predicting Customer Behavior by Just Clicking on the Screen
RecSys 2018
Query-Based Simple and Scalable Recommender Systems with Apache Hivemall