Mark Peng
1 SlideShare 69 Followers
Personal Information
Organization / Workplace
New Taipei City, Taiwan Taiwan
Occupation
Big Data Scientist
Industry
Technology / Software / Internet
Website
http://mark-peng.blog.ntu.edu.tw/
About
Strong cross-domain abilities in resolving critical technical issues through deep research and solution design. A Kaggle Master - Ranked top 300th place of 393,443 competitors around the world (
Contact Details
Tags
ensemble learning data science big data machine learning kaggle
See more

Presentations

(1)

General Tips for participating Kaggle Competitions

9 years ago • 86951 Views

Likes

(40)
See all

Tips and tricks to win kaggle data science competitions

Darius Barušauskas • 8 years ago

Notes from Coursera Deep Learning courses by Andrew Ng

Tess Ferrandez • 7 years ago

[系列活動] 一天搞懂對話機器人

台灣資料科學年會 • 8 years ago

Automatic time series forecasting

Rob Hyndman • 11 years ago

孔令傑/貓都學得會的手機維修資料分析

台灣資料科學年會 • 9 years ago

Scaling MQTT With Apache Kafka

kellogh • 11 years ago

Deep Learning for Natural Language Processing: Word Embeddings

Roelof Pieters • 9 years ago

Istanbul Spark Meetup Nov 28 2015

Chris Fregly • 9 years ago

Cassandra via-docker

Chris Ballance • 9 years ago

Why your Spark job is failing

Sandy Ryza • 10 years ago

Codetainer: a Docker-based browser code 'sandbox'

Jen Andre • 9 years ago

Kinesis vs-kafka-and-kafka-deep-dive

Yifeng Jiang • 9 years ago

DataStax NYC Java Meetup: Cassandra with Java

carolinedatastax • 11 years ago

Linux Profiling at Netflix

Brendan Gregg • 10 years ago

Streaming Big Data with Spark, Kafka, Cassandra, Akka & Scala (from webinar)

Helena Edelson • 10 years ago

Time series with Apache Cassandra - Long version

Patrick McFadin • 11 years ago

Apache cassandra & apache spark for time series data

Patrick McFadin • 10 years ago

Analyzing Time Series Data with Apache Spark and Cassandra

Patrick McFadin • 10 years ago

Applied Machine Learning for the IoT - Data Science Pop-up Seattle

Domino Data Lab • 9 years ago

Understanding Feature Space in Machine Learning - Data Science Pop-up Seattle

Domino Data Lab • 9 years ago

Collaborative Filtering with Spark

Chris Johnson • 11 years ago

Matrix Factorization Techniques For Recommender Systems

Lei Guo • 13 years ago

Apache Kafka 0.8 basic training - Verisign

Michael Noll • 11 years ago

Scaling Through Partitioning and Shard Splitting in Solr 4

thelabdude • 12 years ago

The Many Facets of Apache Solr - Yonik Seeley

lucenerevolution • 13 years ago

Tips for data science competitions

Owen Zhang • 10 years ago

The Universal Recommender

Pat Ferrel • 10 years ago

Feature Importance Analysis with XGBoost in Tax audit

Michael BENESTY • 10 years ago

Boosting Documents in Solr by Recency, Popularity and Personal Preferences - By Timothy Potter

lucenerevolution • 14 years ago

Winning data science competitions, presented by Owen Zhang

Vivian S. Zhang • 10 years ago
Personal Information
Organization / Workplace
New Taipei City, Taiwan Taiwan
Occupation
Big Data Scientist
Industry
Technology / Software / Internet
Website
http://mark-peng.blog.ntu.edu.tw/
About
Strong cross-domain abilities in resolving critical technical issues through deep research and solution design. A Kaggle Master - Ranked top 300th place of 393,443 competitors around the world (
Tags
ensemble learning data science big data machine learning kaggle
See more