Follow @continuumio on Twitter

Schedule

Boston Main Conference

Schedule for July 27, 2013

Time Track 1 Intermediate/Advanced Talks Track 2 Track 3
9:30 a.m.
10:30 a.m.
Andrew Giessel (Harvard Medical School)
Beginner NumPy Tutorial
Michael Becker (AWeber)
Intro to scikit-learn
Satrajit Ghosh (McGovern Institute for Brain Research, MIT)
Python Tools for Reproducible Research in Brain Imaging
11:20 a.m.
Michael Becker (AWeber)
Realtime Predictive Analytics Using RabbitMQ & scikit-learn
Adrian Heibut (Broad Institute)
Grizzly: Reverse-engineering Cancer and Brain Development with Multidimensional Dataflow Programming
12:10 p.m.
James Powell (NYC Python) , Saul Diez-Guerra (Ampush)
My First Numba
David Weisman (Data Scientist)
PYDATA AFTER PARTY
Zak Fallows (Medica)
Cython: Readable like Python, fast like C
1:00 p.m.
Justin Sun (World Travel Holdings)
Orange Canvas
TBD
TBD
1:20 p.m.
Talk
2:20 p.m.
Wen-ming Ye (Microsoft)
Python and Windows Azure
Robert Speer (Luminoso / ConceptNet)
How does text become data?
Alex Rubinsteyn (NYU)
Parakeet
3:10 p.m.
Lynn Cherny (Ghostweather R & D)
Bestseller Analysis: Sex Scene Detection, Topics, and Pacing
Demian Wassermann (BWH Harvard)
DX Analytics -- A Python-based Library for Derivatives Analytics
4:00 p.m.
Jonathan Jesneck (Essess)
Personalizing spatial search by blending machine learning and spatial statistics
Eric Jonas (Salesforce)
Discovering Hidden Structure in Data with Latent Variable Models in Python
Chris Colbert (JP Morgan )
Sentiment Classification Using scikit-learn
4:40 p.m.
Talk
5:00 p.m.
Thomas Wiecki (Quantopian)
Financial Analysis in Python
James Powell (NYC Python)
Embeddings of Python
Cam Davidson-Pilon (Shopify)
Know Thy Neighbor: An Introduction to Scikit-learn and K-NN

Schedule for July 28, 2013

Time Track 1 Intermediate/Advanced Talks Track 2 Track 3
8:30 a.m.
Talk
9:30 a.m.
Cathy O'Neil
Senior Data Scientist, Johnson Research Labs
Know Thy Neighbor: An Introduction to Scikit-learn and K-NN
10:30 a.m.
Ian Stokes-Rees (Continuum Analytics)
Tutorial on Data Analytics with IPython and Wakari
James Powell (NYC Python)
Dataflow Programming Using Generators and Coroutines
Juan Pedro Fisanotti (Machinalis)
SimpleAI (Artificial Intelligence Python lib)
11:15 a.m.
Thom Neale (Sunlight Foundation)
Citation Network Analysis
Justin Riley (MIT Office of Digital Learning)
Starcluster - Cluster Computing Toolkit for the Amazon EC2 Cloud
12:00 p.m.
Skipper Seabold
Introduction to Data Wrangling with pandas
Jonathan Jesneck (Essess)
Negawatt mapping: city-scale energy analytics
Austin Ogilvie (Yhat) , Greg Lamp (Yhat)
Predictive model deployment with Yhat
12:45 p.m.
Matei Zaharia (MIT)
PySpark: Fast and Expressive Big Data Analytics from Python
Andrew Giessel (Harvard Medical School)
Analytical Tools for Circuit Neurobiology
1:25 p.m.
Lunch
2:20 p.m.
Chris Halpert (Meetup.com)
Speed without drag
Imri Sofer (Serre Lab, Brown University)
Bayesian data analysis using PyMC
Michael Sun (Jumptap)
An Introduction to Pydoop: The Python Interface to Hadoop
3:10 p.m.
Bryan Lewis (Paradigm4) , Travis Oliphant (Co-Founder & CEO, Continuum Analytics)
Pythran: Static Compiler for High Performance
Vipin Sachdeva (IBM)
Comparing R and Python for PCA Analysis
Ben Lerner (DataNitro)
Introduction to DataNitro: Python in Excel
3:50 p.m.
Break & Snacks
4:20 p.m.
Jeff Bezanson (Julia)
Julia
Ian Stokes-Rees (Continuum Analytics)
Importing and Analyzing SQL Data With the Django ORM
Craig Schmidt (Predictobot)
DataPad: Python-powered Business Intelligence
5:10 p.m.
Lightning Talks