Open Source Tools & Data Science Competitions

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This talk shares the presenter’s experience with open source tools in data science competitions. In the past several years Kaggle and other competitions have created a large online community of data scientists. In addition to competing with each other for fame and glory, members of this community also generously share knowledge, insights using forum and open source code. The open competition and sharing have resulted in rapid progress in the sophistication of the entire community. This presentation will briefly cover this journey from a competitor’s perspective, and share hands on tips on some open source tools proven popular and useful in recent competitions.

Technology

OPEN SOURCE
TOOLS & DS
COMPETITIONS
Owen Zhang
O P E N
D A T A
S C I E N C E
C O N F E R E N C E_
BOSTON
2015
@opendat
asci

Open Source Tools & Data Science Competitions

Our fall 12-Week Data Science bootcamp starts on Sept 21st,2015. Apply now to get a spot! If you are hiring Data Scientists, call us at (1)888-752-7585 or reach info@nycdatascience.com to share your openings and set up interviews with our excellent students. --------------------------------------------------------------- Come join our meet-up and learn how easily you can use R for advanced Machine learning. In this meet-up, we will demonstrate how to understand and use Xgboost for Kaggle competition. Tong is in Canada and will do remote session with us through google hangout. --------------------------------------------------------------- Speaker Bio: Tong is a data scientist in Supstat Inc and also a master students of Data Mining. He has been an active R programmer and developer for 5 years. He is the author of the R package of XGBoost, one of the most popular and contest-winning tools on kaggle.com nowadays. Pre-requisite(if any): R /Calculus Preparation: A laptop with R installed. Windows users might need to have RTools installed as well. Agenda: Introduction of Xgboost Real World Application Model Specification Parameter Introduction Advanced Features Kaggle Winning Solution Event arrangement: 6:45pm Doors open. Come early to network, grab a beer and settle in. 7:00-9:00pm XgBoost Demo Reference: https://github.com/dmlc/xgboost

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Tong is a data scientist in Supstat Inc and also a master students of Data Mining. He has been an active R programmer and developer for 5 years. He is the author of the R package of XGBoost, one of the most popular and contest-winning tools on kaggle.com nowadays. Agenda: Introduction of Xgboost Real World Application Model Specification Parameter Introduction Advanced Features Kaggle Winning Solution

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