Robin Su, Consultant, teradata at Teradata

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Frontiers of Natural Language Processing

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IoT State of the Union - IOT210 - re:Invent 2017

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Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text classification and similarity

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Using Text Embeddings for Information Retrieval

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Steffen Rendle, Research Scientist, Google at MLconf SF

MLconf • il y a 9 ans

Algorithmic Music Recommendations at Spotify

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行銷企劃實戰力 Marketing Planning

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Collaborative Filtering at Spotify

Erik Bernhardsson • il y a 11 ans

Interactive Recommender Systems with Netflix and Spotify

Chris Johnson • il y a 8 ans

Matrix Factorization In Recommender Systems

YONG ZHENG • il y a 9 ans

Building a modern Application with DataFrames

Spark Summit • il y a 8 ans

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Young Yang • il y a 6 ans

[系列活動] 一天搞懂對話機器人

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Spark Summit • il y a 8 ans

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

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Reversim Summit 2014: re:dash a new way to query, visualize and collaborate on data

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台灣資料科學年會 • il y a 7 ans

Robin Su

Présentations

real-time Web的運用

J’aime

Deep Learning for Recommender Systems

生成對抗模式 GAN 的介紹

Time Series with Driverless AI - Marios Michailidis and Mathias Müller - H2O AI World London 2018

Deep Learning for Recommender Systems RecSys2017 Tutorial

Frontiers of Natural Language Processing

AWS物聯網基礎架構及連線概覽

IoT State of the Union - IOT210 - re:Invent 2017

Embed, Encode, Attend, Predict – applying the 4 step NLP recipe for text classification and similarity

A Simple Introduction to Word Embeddings

Using Text Embeddings for Information Retrieval

It's Not Magic - Explaining classification algorithms

Steffen Rendle, Research Scientist, Google at MLconf SF

Algorithmic Music Recommendations at Spotify

行銷企劃實戰力 Marketing Planning

Collaborative Filtering at Spotify

Interactive Recommender Systems with Netflix and Spotify

Matrix Factorization In Recommender Systems

Building a modern Application with DataFrames

Resilience is by design

[系列活動] 一天搞懂對話機器人

Sparking Science up with Research Recommendations by Maya Hristakeva

Recommender Systems (Machine Learning Summer School 2014 @ CMU)

[系列活動] 使用 R 語言建立自己的演算法交易事業

Reversim Summit 2014: re:dash a new way to query, visualize and collaborate on data

大型 Web Application 轉移到微服務的經驗分享

Research 101 - Paper Writing with LaTeX

Building an Effective Data Warehouse Architecture

網路購書大數據– 給出版者的洞察分析

How to Deliver Powerful Personalized Experiences

[系列活動] 人工智慧與機器學習在推薦系統上的應用