Anatomy of Decision Trees using an example from Kaggle

Jul 2015

13 Mon

14 Tue

15 Wed

16 Thu 08:30 AM – 06:35 PM IST

17 Fri 08:30 AM – 06:30 PM IST

18 Sat 09:00 AM – 06:30 PM IST

19 Sun

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NIMHANS Convention center

Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.

The deadline for submitting a proposal is 15th June 2015

We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.

Track 1: Discovering Insights and Driving Decisions

This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:

Statistical Visualizations
Unsupervised Learning
Supervised Learning
Semi-Supervised Learning
Active Learning
Reinforcement Learning
Monte-carlo techniques and probabilistic programming
Deep Learning

Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.

Track 2: Speed at Scale

This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:

Distributed and Parallel Computing
Real Time Analytics and Stream Processing
MapReduce and Graph Computing frameworks
Kafka, Spark, Hadoop, MPI
Stories of parallelizing sequential programs
Cost/Security/Disaster Management of Data

HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.

Workshops

If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.

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The Fifth Elephant

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

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Anatomy of Decision Trees using an example from Kaggle

Submitted Jun 15, 2015

Section: Full Talk Technical level: Intermediate

Decision trees are amongst the most popular predictive modelling techniques in the analytics industry. Attendees will learn how to effectively apply decision trees to predict survival on the Titanic: Machine Learning from Disaster problem in Kaggle.

Outline

Attendees will learn about practical considerations for predictive modelling using Decision Trees, Bagging, Boosting, Random Forest using a simple example from Kaggle. The session will include slide presentation accompanied with demonstration using R and Rapidminer. Participants should be familiar with basics of predictive analytics including classification.

Requirements

Attendees would not need to bring anything.

Speaker bio

Saurabh is a Senior Specialist at Sapient Global Markets. He has 20 years of industry experience in technology consulting and product development in USA and India. Saurabh’s domain experience includes Financial Services, Healthcare and Telecom. In his current role, he is responsible for driving sales, delivery and innovation efforts in Data Analytics space at Sapient Global Markets.

Prior to Sapient, Saurabh worked with PwC as Associate Director, Strategy & Architecture practice. He is passionate about machine learning and understanding its impact on businesses, world economy and future generations.