QuantumBlack: Kedroを用いた実践的なデータパイプライン開発とモデル構築

This is a past event

53 people went

McKinsey & Company

Minato City, Roppongi, 1-chōme−9−10 · Tōkyō-to

How to find us

一階で受付します。最寄駅:南北線・銀座線「溜池山王駅」徒歩4分/南北線「六本木一丁目駅」徒歩4分 32nd floor. Please register on the first floor. Nearest Train Station: 4 minute walk from Tameike-sanno Station (Nanboku Line, Ginza Line) / 4 minute walk from Roppongi-itchome Station (Nanboku Line)

Location image of event venue


QuantumBlack Japan Meetup #2
Presented by QuantumBlack, a McKinsey Company
Free event with drinks and food provided

19:00-19:15  ネットワーキング
19:15-19:20 オープニング
19:20-20:20 Kedroを用いた実践的なデータパイプライン開発とモデル構築
20:20-21:00 ネットワーキング

●スピーカー: ジュニアプリンシパルデータエンジニア 小島剛
QuantumBlack, a McKinsey Company



kedroを用いた機械学習モデルの開発過程を Hands-on デモによりウォークスルーします。

* 重要事項

19:00-19:15 Networking
19:15 -19:20 Opening
19:20-20:20 Presentation
20:20-21:00 Networking

Go Kojima, Junior Principal Data Engineer
QuantumBlack, a McKinsey Company

Title: Practical data pipeline and analytical model development using Kedro

Summary: Kedro is an open-source software by QuantumBlack: https://github.com/quantumblacklabs/kedro
Kedro is an open data source for QuantumBlack, a data pipeline framework designed to enable teams of data scientists and engineers to develop models from the data pipeline.
We will walk through the process of developing a machine learning model using Kedro with a hands-on demo.

What to bring:
- Passion in data analytics!
- Government-issued ID to show security to get access to the building
- Business card

* Important information
- You can join this event for free.
- Please bring your business card or your indentification.
- This presentation will be in Japanese, and Q&A is also possible in English.

Use of data and privacy:
By participating in the [meetup] you agree that McKinsey & Company may (i) videotape, audiotape, photograph, or otherwise record your name, voice, or image, and (ii) use and distribute such videotapes, audiotapes, photographs or recordings of your name, voice or image in any texts, videos, and other materials that McKinsey may make available through websites and social media to its employees or any third parties.

If you do not wish to be recorded please inform the event organizer in advance.