Notes on Takuya Kitazawa

I have recently studied data visualization with D3.js and React from Datavis 2020 by Curran Kelleher.

Over the past few years, I have been using LaTeX for writing a resume.

Everyone wants to leverage machine learning (ML) in their daily work, and I'm sure they will be excited about your awesome ML product whatever the detail is.

As I wrote in Don't "Guess" How People in Other Roles Work, I have been studying something new in my spare time, and the two online courses I have recently accomplished, Visual Elements of User Interface Design and UX Design Fundamentals, told me an impor…

Spend a bit of your time to "learn" what they do, and talk to them, instead.

I have earned my certificate of Functional Programming in Scala Specialization completion.

What does define "professional" mean?

We have spent more than a month since working-from-home (WFH) accidentally becomes a global trend.

A good dashboard is all we need — As a person working in the field of data-driven business, I strongly agree with the statement written in "One Thing to Maybe Build Now: A Great Dashboard".

Recently, I dropped off my iPhone from my hand, and the screen has partially been broken.

In How to Produce Ideas, I emphasized the importance of gathering as much information as possible from a wide variety of sources.

As an engineer, I've been working on machine learning (ML) and data science at Arm Treasure Data over the past three years.

Everyone loves design thinking, a systematic way of problem-solving, and, in practice, the approach suggests non-designers to undergo the following steps to efficiently and effectively build valuable solutions: Empathize with users.

My 2020 has been kicked off with NRF 2020, one of the world's largest retail conferences.

Producing ideas is an important process of creating something new (e.g., business, product, software, article), but its methodology is not trivial.

October 2019 was a big month!

After my speaking session at ApacheCon Europe in Berlin, luckily I've got a chance to attend Day 2 sessions of Data Leaders Summit Europe: https://twitter.com/takuti/status/1187262382944538624 As the name suggests, speakers and audiences of the summit are…

As a committer/PPMC of Apache Hivemall (incubating), I have attended and presented at ApacheCon North America and ApacheCon Europe.

From March 2019 to July 2019, I experimentally stopped drinking alcohol alone.

For the recent two years, I have used GitHub Pages to publish my takuti.me site built by Hugo: Moving to GitHub Pages Deploying Static Site to GitHub Pages via Travis CI Meanwhile, this article you are reading is distributed by Netlify as of Aug 31, 2019.

I have attended and presented at JuliaCon 2019 held in Baltimore, MD, USA: Recommendation.jl: Building Recommender Systems in Julia Recording is available at YouTube: The 10-min lightning talk was very short.

It has been a month since I presented at The 27th ACM Conference On User Modeling, Adaptation And Personalization (UMAP2019) held in Larnaca, Cyprus: Zero-Coding UMAP in Marketing: A Scalable Platform for Profiling and Predicting Customer Behavior by Just…

TokuDB is a high-performance, scalable storage engine for MySQL/MariaDB.

When I was a master's student, I had developed Recommendation.jl, a collection of well-known recommendation techniques written in Julia: Recommendation.jl: Building Recommender Systems in Julia Recently I have been working on creating its documentation si…

Apache Hivemall, a collection of machine-learning-related Hive user-defined functions (UDFs), offers Spark integration as documented here.

Streaming recommendation is one of the most challenging topics in the field of recommender systems.

I have attended MLconf 2018 in San Francisco.

Arm Pelion IoT Platform makes the Mbed ecosystem much more sophisticated and enables us to seamlessly manage IoT connectivity, device and data at a unified place: Treasure Data: A Pelion data management service My recent experience at Mbed Connect USA tel…

Apache Hivemall is a scalable machine learning library running on top of the Hadoop ecosystem, and you can freely enjoy its functionalities in your Apache Hive or Spark environment.

The field of recommender systems grows rapidly according to the recent development of practical intelligent systems.

As I repeatedly mentioned in this blog, takuti.me is currently generated by Hugo: Migrate to Hugo from Jekyll: Another Solution for the MathJax+Markdown Issue Moving to GitHub Pages Hugo meets kramdown + KaTeX #gohugo Manual deployment Until quite recentl…

Recently, math rendering library in this page, takuti.me, has been switched from MathJax to KaTex to improve performance.

takuti.me is currently generated by Hugo, a fast static site generator written in Go, as I introduced a year and a half ago.

Resilient Distributed Dataset (RDD) is a distributed parallel data model in Spark.

What is the difference between parallel programming and concurrent programming?

Last week, I introduced a Julia package for recommender systems: Recommendation.jl: Building Recommender Systems in Julia.

I have recently published Recommendation.jl, a Julia package for recommender systems.

In this year, I focus on writing more and more articles on this blog.

Migrate to Hugo from Jekyll I had used Jekyll to generate this site for 1+ years.

Following phpcon2015, I have attended PyCon JP 2015 at the end of last week.

I have attended phpcon2015, Japan PHP Conference 2015, on October 3.

Hi, I am takuti, a master's student in Japan.

In the linear regression tasks, the normal equation is widely used to find optimal parameters.

Hi, I'm takuti.