June 17-18, 2016Venue:
Asia Pacific College, 3 Humabon Place, Magallanes, Makati City Location MapHow Will You Benefit?
- Learn the skills of a Data Scientist, The Best Job To Pursue In 2016
accordingto Forbes Magazine
- Apply Machine Learning in yourorganization after 2 days using one ofthe best open-source softwareavailableWho Should Attend?
- Current and Aspiring Data Scientists
- Analysts and OR Practitioners
- Anyone interested to learn Machine LearningWhat You Will Learn?
- Learn the basic Machine Learning algorithms
- Learn how to use KNIME, an Open Source Analytics Platform that does not require coding!
- Apply Machine Learning algorithms in real-world problems including Sentiment Analysis, Document Retrieval, Product Recommendation, Text Classification, Clustering and more!What is KNIME?
KNIME (pronounced/naɪm/), the Konstanz Information Miner, is an Open Source data analytics, reporting and integration platform.
It has been rated #1in satisfaction foropen sourceanalytics platforms. (Source:https://www.knime.org/No1Satisfaction
Unlike other analytics software, KNIME does not require any coding.It uses a graphical workflow interface for data preprocessing, for modeling, data analysis and visualization.SEMINAR INFORMATIONSeminar Timing :
June 17 – 18, 2016Registration:
7:30 am Course proper:
8:00 am – 5:00 pm.
15 minute morning and afternoon breaks at 10:00 am and 3:00 pm.
Lunch 12:00 – 1:00 pm.Venue :
Asia Pacific College, 3 Humabon Place, Magallanes, Makati CityREGISTRATION FEES
*Fee includes seminar fee, handouts, use of computer lab, am/pm snacks and lunch for 2 days
Fees in Pesos
Early Bird Rate
(Before April 30)
(May 1 - June 12)
Please call or email ORSP at +632 439 9496 or firstname.lastname@example.org
c/o Jenny .PAYMENT DETAILS:
Please deposit cash or check to:Account Name:
Operations Research Society of the Philippines (please do not abbreviate)Account No:
Banco de Oro - Libis
Please email or fax your deposit slip with this registration form to ORSP Secretariat office c/o Jenny, telefax 02 439 9496; mobile 0927 877 521 ; e-mail:email@example.com