Conference Schedule

Talks Tutorials Discussions

Keynotes and Invited Speakers — Nov. 9, 2015

08:00AM Registration and Breakfast ---
09:00AM Python as the Zen of Data Science Travis Oliphant , Peter Wang
10:00AM How Python Found its way Into Astronomy Perry Greenfield
10:55AM Memex: Mining the Dark Web Katrina Riehl
11:50AM The Future of Machine Learning Panel Discussion Andreas Mueller, Jared Lander, Julia Lintern
12:35PM Lunch ---
01:35PM The Pain of Discipline and the Power of Not Yet Cornelia Levy-Bencheton
02:30PM Julia for Data Analysis and Beyond Stefan Karpinski
03:15PM Break and Snacks ---
03:30PM New Project Features- scikit-learn, pandas, matplotlib, & jupyter Andreas Mueller, Brian Granger, Jeff Reback, Michael Droettboom
04:35PM Lightning Talks ---

Tutorials and Talks — Nov. 10, 2015

  A B C 1 2
08:00AM Registration and Breakfast ---
09:00AM matplotlib Michael Droettboom Python Epiphanies Stuart Williams Neural networks with Theano and Lasagne Eben Olson
10:40AM Getting Started with Machine Learning Applications Rajat Arya, Brian Kent Using Python in Visual Studio Steve Dower Mining Georeferenced Data: Location-based Services and the Sharing Economy Bruno Gonçalves, Anastasios Noulas
12:10PM Lunch ---
01:10PM Towards a universal platform for data science on public and private clouds Karim Chine Reproducibility of your development environment Marcos Vanetta Beating Python's GIL to Max Out Your CPUs Andrew Montalenti - An exploration of K-Means clustering of NYC Taxis in Manhattan Gregory Kamradt A Pipeline for Modeling Automated Scoring Using Python, R and Jupyter Notebooks Nitin Madnani
01:55PM Portfolio and Risk Analytics in Python with pyfolio Dr. Jessica Stauth Density-Based Clustering in Python Brian Kent Social Science-Conscious Analysis Case Study: The Cost of Public School In NYC Riley H Understanding Product Attributes From Reviews Sanghamitra Deb Using Graphs for High Quality Recommendations amit bhattacharyya
02:45PM Bootstrapping Applications and Dashboards with IPython Widgets Andrew Campbell Visualizing Wireless-Router Timeseries Data with the Density API, Seaborn, and Pandas Jessica Forde Using Django as a data tool in the Enterprise. Trent Oliphant Using Massive Passive Phone Calling Data to Understand and Predict Human Mobility Fahad Alhasoun Data Workflows - Getting Repeatable Results in Data Science Rob Parrish
03:25PM Break and Snacks ---
03:40PM Jupyter Brian Granger Correlation Matrix Filtering and Asset Allocation with Python Steve Taylor Word embeddings as a service Francois Scharffe TinkerPop and Titan from a Python State of Mind Denise Gosnell, PhD, Brian Corbin Global Botnet Detector Brenton Mallen
04:25PM Understanding Probabilistic Topic Models By Simulation Timothy Hopper Simplifying large scale parallel processing with Storm and streamparse Dan Blanchard Exploring temporal graph data with Python: a study on tensor decomposition of wearable sensor data Andre Panisson A Deep Dive into R for Python Developers Robert Aboukhalil Exploring Github's Programming Languages using Machine Learning and Network Analysis Amirali Sanatinia
05:05PM Great Taste, Less Wordy: Document Summarization of Beer Reviews Ben Fields A survey of Python interpreters Brett Cannon Binder: sharing and reproducing computation Andrew Osheroff, Jeremy Freeman, Kyle Kelley Parallel Programming in Python: Speeding up your analysis Manojit Nandi How do we know if it was hot today? Quantifying qualitative measures of weather Michal Monselise

Tutorials and Talks — Nov. 11, 2015

  A B C 1 2
08:00AM Registration and Breakfast ---
09:00AM Machine Learning with scikit-learn Andreas Mueller Building interactive visualization with VTK, Matplotlib and Enaml Pawel Potocki Network Analysis Fundamentals Eric J. Ma
10:40AM D3 in Jupyter Brian Coffey Performance Pandas Jeff Reback Scrapy Workshop Karthik Ananth
12:10PM Lunch ---
01:10PM Optimize your Docker Infrastructure with Python Ryan J. O'Neil Realtime Risk Management Using Kafka, Python, and Spark Streaming Nick Evans How Big Data is transforming biology and how we are using Python to make sense of it all. Maria Nattestad One of these things is not like the others. Automatically detecting outliers. Homin Lee Python with a SWIG of C++ Bob McNaughton
01:55PM Production and Beyond: Deploying and Managing Machine Learning Models Shawn Scully Blaze: An Interface to all the Things Phillip Cloud The Art and Science of Data Matching Mike Mull An iterative approach to inverse problems using Python's NumPy Katya Vasilaky Beating the world's traffic with Machine Learning Yam Peleg
02:45PM Querying 1.6 billion reddit comments with python Daniel Rodriguez Python Libraries for Deep Learning with Sequences Alex Rubinsteyn Does Code Quality Really Matter? James Powell A next generation live tick database accessible through Python, backed by SciDB Jonathan Rivers Getting Started in Computational Sociology with Python Tara Adiseshan
03:25PM Break and Snacks ---
03:40PM Dask - Parallelizing NumPy/Pandas through Task Scheduling Jim Crist Song Matching by Analyzing and Hashing Audio Fingerprints With Python Scientific Stack and SQL DB Milos Miljkovic Lightning: Web-First Data Visualization in Python Matthew Conlen Challenges of building a Short Term Trading Simulator and Trading Models Shayne Young Building a Financial Data Warehouse Solmaz Shahalizadeh
04:25PM Developing an Expression Language for Quantitative Financial Modeling Scott Sanderson Deep Style TJ Torres Optimizing Life: Everyday Problems Solved with Linear Programing in Python Anna Nicanorova Using your powers for good: Data science in the social sector Peter Bull Fraud, Fun, and Fortune in event log analytics en zyme, Feyzi Bagirov
05:05PM Lightning Talks ---

Discussion Track

Due to the extremely high quality and large number of submissions for PyData NYC, we have created a Discussion Track featuring workshop-style presentations in two smaller rooms. This Discussion Track will take place alongside our regular talk & tutorial tracks.

PLEASE NOTE: The Discussion Track will unfortunately not be recorded.