Intro to Text Mining Using tm, openNLP and topicmodels – Ted Kwartler ODSC Boston 2015
Intro to Text Mining Using tm, openNLP and topicmodels from odsc You will learn how modern customer service organizations use data to understand important customer attributes and how R is used for workforce optimization. Topics include real world examples of how R is used in large scale operations to... Read more
Monary: Really fast analysis with MongoDB and NumPy – Anna Herlihy ODSC Boston 2015
Monary from odsc “MongoDB is a scalable, flexible and easy to use way of storing large data sets. Python and NumPy provide a comprehensive toolkit for data analysis. Unfortunately they don’t work together as well as they could: the official Python driver for MongoDB, PyMongo, is inefficient at loading... Read more
Frontiers of Open Data Science Research – Ani Aghababyan ODSC Boston 2015
Frontiers of Open Data Science Research from odsc Keynote Presenter Bio Ani loves writing about herself in third person and has written this all true bio. Ani is a Data Scientist for the Digital Platforms Group in McGraw-Hill Education company. She has a diverse educational background (some say she... Read more
Data Science 101 – Todd Cioffi ODSC Boston 2015
Data Science 101 from odsc Curious about Data Science? Self-taught on some aspects, but missing the big picture? Well, you’ve got to start somewhere and this session is the place to do it. This session will cover, at a layman’s level, some of the basic concepts of Data Science.... Read more
The Art of Data Science – Josh Wills ODSC Boston 2015
The Art of Data Science from odsc Keynote Presenter Bio Josh Wills is Cloudera’s Senior Director of Data Science, working with customers and engineers to develop Hadoop-based solutions across a wide-range of industries. He is the founder and VP of the Apache Crunch project for creating optimized MapReduce pipelines... Read more
Can We Automate Predictive Analytics – Thomas Dinsmore ODSC Boston 2015
Can We Automate Predictive Analytics from odsc Recent news about the pending shortage of data scientists prompts speculation about automation: will machines replace human analysts? We propose a model of automation, and briefly review progress in automated machine learning over the past twenty years. Summarizing the current state of... Read more
Opening the Doors to Innovation in Developing Countries through the Democratization of Data – Ari Hamalian ODSC Boston 2015
Opening the Doors to Innovation Through the Democratization of Data from odsc Initiatives such as a Wikipedia and the Human Genome Project have demonstrated the multiplicative positive impact that data can have when shared openly. Increasingly countries and governments across the globe have begun to embrace and recognize the... Read more
Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of Data-Parallel Graph Analytics (Application to Bioinformatics) – Brad Bebee ODSC Boston 2015
Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of Data-Parallel Graph Analytics (Application to Bioinformatics) from odsc From social networks to protein networks to financial transactions, graphs are everywhere. Graph Analytics represent a key tool for data science to take advance of this type of network information. Many... Read more
Learning to Love Bayesian Statistics – Allen Downey ODSC Boston 2015
http://tinyurl.com/lovebayes Bayesian statistical methods provide powerful tools for answering questions and making decisions. For example, the result of Bayesian analysis is a set of values and probabilties that can be fed directly into a cost-benefit analysis, which is not possible with conventional statistics. But there are several barriers to... Read more
Data Workflows for Iteration, Collaboration, and Reproducibility – David Chudzicki ODSC Boston 2015
http://www.davidchudzicki.com/slides/odsc-2015-workflow/ For other data scientists to improve, build on, or even just trust your analysis, they need to be able to reproduce it. Even if you have shared code and data, reproducing your analysis may be difficult: which code was executed against which data in what order? And even... Read more