Andre Pemmelaar
2 SlideShares 14 Followers 12 Followings
Personal Information
Organization / Workplace
Japan Japan
Occupation
Financial algorithms, systematic trading, machine learning
Industry
Finance / Banking / Insurance
Website
quoine.com/
About
Leading the team developing the cryptocurrency world's next generation algorithmic liquidity provision engine. • Low latency market making algorithms • Artificial intelligence in the service of liquidity provision • Smart order routing for the cryptocurrency world • Large-scale distributed financial data infrastructure
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Tags
julialang lstm long-term short-term memory recurrent neural networks rnn julia language expression graphs automatic differentiation time series sequence models machine learning financial systems julia data science data analytics
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Presentations

(2)

Julia language: inside the corporation

10 years ago • 7435 Views

Generating Sequences with Deep LSTMs & RNNS in julia

10 years ago • 7260 Views

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(27)
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IOTA - Tokyo Meetup 2017-11-09

🌍 Norbert Gehrke • 7 years ago

Building an AI Startup: Realities & Tactics

Matt Turck • 8 years ago

10 more lessons learned from building Machine Learning systems

Xavier Amatriain • 9 years ago

闇と向き合う

Nagi Teramo • 9 years ago

7 ineffective coding habits many F# programmers don't have

Yan Cui • 9 years ago

スタートアップを始める前に

Takaaki Umada • 9 years ago

Apache Sparkの紹介

Ryuji Tamagawa • 9 years ago

ggplot2再入門（2015年バージョン）

yutannihilation • 9 years ago

Sparkパフォーマンス検証

BrainPad Inc. • 10 years ago

続わかりやすいパターン認識11章(11.1 - 11.4)

Nagi Teramo • 10 years ago

Life Beyond the Illusion of Present

Jonas Bonér • 10 years ago

20150414seminar

nlab_utokyo • 10 years ago

Recurrent Neural Networks

Seiya Tokui • 10 years ago

Domain Driven Design with the F# type System -- F#unctional Londoners 2014

Scott Wlaschin • 11 years ago

Haskell vs. F# vs. Scala

pt114 • 12 years ago

Ultra Lightning Talk × 3

Nagi Teramo • 10 years ago

F#談話室(17)

Nagi Teramo • 10 years ago

10 Lessons Learned from Building Machine Learning Systems

Xavier Amatriain • 10 years ago

Spark MLlibではじめるスケーラブルな機械学習

NTT DATA OSS Professional Services • 10 years ago

RFinanceJはじめました

Nagi Teramo • 10 years ago

Julia language: inside the corporation

Andre Pemmelaar • 10 years ago

#Julialang and Computer Shogi (Japanese Chess)

Takeshi Kimura • 11 years ago

MBrace: Cloud Computing with F#

Eirik George Tsarpalis • 11 years ago

Information-Rich Programming in F# with Semantic Data

Steffen Staab • 11 years ago

Bnlearn tokyo r29th

Kentaro Taguchi • 12 years ago

Production machine learning_infrastructure

joshwills • 11 years ago

F# in social gaming

Yan Cui • 11 years ago
Personal Information
Organization / Workplace
Japan Japan
Occupation
Financial algorithms, systematic trading, machine learning
Industry
Finance / Banking / Insurance
Website
quoine.com/
About
Leading the team developing the cryptocurrency world's next generation algorithmic liquidity provision engine. • Low latency market making algorithms • Artificial intelligence in the service of liquidity provision • Smart order routing for the cryptocurrency world • Large-scale distributed financial data infrastructure
Tags
julialang lstm long-term short-term memory recurrent neural networks rnn julia language expression graphs automatic differentiation time series sequence models machine learning financial systems julia data science data analytics
See more