Name: TMLS#3 Applying Deep Learning
Start: 2016-05-27T19:00:00+09:00
End: 2016-05-27T22:00:00+09:00
Location: Google's Office

Hello everyone,

We are very excited to announce the third TMLS event of 2016 is coming up on 5/27! Please leave your Friday night open, we have invited amazing speakers to discuss some of the latest deep learning technologies. The event sign-up opens from 5/19 Thursday @10am. Due to the capacity of the room, general admissions are limited to 100 people. Don't miss!

みなさんこんにちは！2016年第3回目となるTMLSのイベントです。5月27日金曜日の夜、ぜひスケジュールを空けておいてください！参加申し込みは5月19日(木) 10:00amから開始しますので、お見逃しなく！

===================================================

[Vey important information for sign-up]

We are still figuring out the best way to organize this event @ Google Office. We used connpas last time for the RSVP but we found some inconvenience there too. This time we come back to meetup.com. PLEASE STAY ON THIS PAGE AND SIGN-UP FROM HERE! Same as last time,WE NEED YOUR REAL FULL NAME as it appears on your ID to get you into the Mori Tower building. When you sign-up for the event, we will ask you questions. Everyone of you MUST INPUT YOUR ACTUAL NAME as an answer to the question. Please show your ID at the reception desk on the day of the event.

*Make sure the name you sign up with matches the name on your ID!

*You cannot sign-up on behalf of your friends

*You cannot enter the building after 7:30pm

*All the speech will be in English

[参加に関して重要なお知らせ]

前回はconnpassを使いましたが、今回はmeetup.comから参加を受け付けます。今回もGoogle Japanのご協力のもと、六本木ヒルズ森タワーで開催します。入館時には本名(フルネーム) が必要となりますので、イベント申込時の質問には絶対回答してくださいね（お名前を聞きます）！

*必ずIDと一致する名前を回答してください

*本人のみ参加可

*7:30pm以降は入館できません

*全てのプレゼンは英語で行われます

[Win a Google T-shirt!]

Please leave your business card at the reception desk - it's your lottery ticket. At the end of the event, three lucky attendees will win a Google Cloud Platform T-shirt!

[抽選に参加してTシャツをもらおう！]

当日、受付にて名刺お渡しいただいたくと、抽選で３名様にGoogle Cloud Platform Tシャツが当たります！お楽しみに。

===================================================

Here are the list of speakers and topics of the night:

今回のスピーカーとトピックです:

Guest Speaker: Adam Gibson, Co-founder, Skymind (http://www.skymind.io/)

Presentation Topic: Anomaly Detection with Deep LearningPresentation

Abstract: Deep Learning is primarily fueled by use cases from ad tech with computer vision and audio being the primary forms of data being processed.This talk will cover deep learning for log analysis, identifying anomalies in things likeweb logs and sensors.

Guest Speaker: Kaz Sato, Developer Advocate, Cloud Platform, Google

Presentation Topic: Cloud ML & Speech APIPresentation

Abstract: The biggest challenge of Deep Learning technology is the scalability. As long as using single GPU server, you have to wait for hours or days to get the result of your work. This doesn't scale for production service, so you need a Distributed Training on the cloud eventually. Google has been building infrastructure for training the large scale neural network on the cloud for years, and now started to share the technology with external developers. In this session, we will introduce new pre-trained ML services such as Cloud Vision API and Speech API that works without any training. Also, we will look how TensorFlow and Cloud Machine Learning will accelerate custom model training for 10x - 40x with Google's distributed training infrastructure.

Speaker: Stefano and David from Reactive Inc.

Presentation Topic: Character-level textual neural networksPresentation

Abstract: Coming soon

Speaker: Ray Sakai from Reactive Inc.

Presentation Topic: Extending Vision APIPresentation

Abstract: Reducing dimensions / generating data by existing AI or: How I learned to stop worrying about CNN.

今回のゲストスピーカーSkymindのCo-founderであるGibson氏はDeep Learningを使ったログやセンサーの異常検知について

同じくゲストスピーカーのGoogle佐藤氏はCloud MLとSpeech APIについて

StefanoとDavidが文字レベルにおけるテキストニューラルネットワークについてのお話を

RayがVision APIの拡張について発表します！

To find out more about the speakers, please check out our event page. (http://reactive.co.jp/event)

スピーカーについての詳細は、こちらのページをご参照ください！ (http://reactive.co.jp/event)

18:30 ～ 19:00 : Reception

19:00 ～ 19:15 : Keynote from TMLS organizer, Fred Almeida

19:15 ～ 19:40 : Adam Gibson Presentation

19:40 ～ 19:45 : Break

19:45 ～ 20:10 : Kaz Sato Presentation

20:10 ～ 20:35 : Reactive Stefano & David Presentation

20:35 ～ 20:40 : Break

20:40 ～ 21:00 : Reactive Ray Presentation

21:00 ～ 21:05 : Lottery

21:05 ～ 22:00 : After party - enjoy pizza and beer!

Jun Iinuma

Kazuhiko Nishimura

Eric Whiteway

Tokyo Machine Learning Society

Technology

Artificial Intelligence

Salesforce.com

Cloud Computing

CRM/Customer Relationship Management

Big Data

Machine Learning

Data Analytics

SaaS (Software as a Service)

Predictive Analytics

Deep Learning

TMLS#3 Applying Deep Learning

Google's Office

Share

Tokyo Machine Learning Society

TMLS#3 Applying Deep Learning

Tokyo Machine Learning Society

Details

Members are also interested in