- Computer Science: America's Untapped Opportunity by Hadi Partovi (code.org) -- link to video
- Clouded Intelligence by Joseph Sirosh -- link to video
- Keynote: Computation at the edges by Van Lindberg -- link to video
- Data-driven Education and the Quantified Student by Lorena Barba (George Washington University) -- link to video
- A Systems View of Machine Learning by Josh Bloom (UC) -- link to video
- Sparkling Pandas - Letting Pandas Roam on Spark DataFrames by Holden Karau (Apline Data Labs) -- link to video
- Building TaxBrain: Numba-enabled Financial Computing on the Web by T J Alumbaugh (Continuum) -- link to video
- Investigating User Experience with Natural Language Analysis by Stephanie Kim (Apollo Education Group) -- link to video
- Accelerate data analytics and Python performance with Intel® software by Sergey Maidanov (Intel) -- link to video
- Memex: Mining the Dark Web by Katrina Riehl -- link to video
- Who needs users? Just simulate them! by Chris Harland (Microsoft) -- link to video
- The past, present, and future of Jupyter and IPython by Jonathan Frederic (Jupyter) -- link to video
- Mixed-language Python/C++ debugging with Python Tools for Visual Studio by Pavel Minaev (Microsoft) -- link to video
- Saving Lives with Data: Python and Global Health by Kyle Foreman (University of Washington) -- link to video
- From DataFrames to Interactive Web Applications in 10 minutes by Adam Hajari (Next Big Sound) -- link to video
- An Intuitive Introduction to the Fourier Transform and FFT by William Cox (Distil Networks) -- link to video
- Anaconda Cluster Use Case by Peter Steinberg (Continuum) -- link to video
- Straight, White Males Should Advocate for Diversity by Tony Wieczorek (Localytics) -- link to video
- What's coming in Python 3.5 (and why you should be excited) by Steve Dower -- link to video
- Deep Learning with Python: getting started and getting from ideas to insights in minutes by Alex Korbonits (Nuiku) -- link to video
- SFrame and SGraph: Scalable External Memory Data Frame and Graph Structures for Machine Learning by Jay (Haijie) Gu (Dato) -- link to video
- Testing for Data Scientists by Trey Causey -- link to video
- Trend Estimation in Time Series Signals by Bugra Akyildiz (Axial) -- link to video
- When is it good to be bad? How do hockey penalties affect the outcome of the game? by Wendy Grus (INRIX) -- link to video
- Using Python and Azure Machine Learning (Sponsor Talk) by Chris Wilcox (Microsoft) -- link to video
- Panel /Group Discussion: “Using, contributing to, and integrating open source" by Panel -- link to video
- Accelerating the Random Forest algorithm for commodity parallel hardware by Mark Seligman -- link to video
- Supernova Cosmology with python by Rahul Biswas (University of Washington) -- link to video
- Brains & Brawn: the Logic and Implementation of a Redesigned Advertising Marketplace by Stephanie Tzeng & Sal Rinchiera (AppNexus) -- link to video
- Blaze and Odo by Phillip Cloud (Enthought) -- link to video
- Hack the Derivative by Erik Taubeneck (GameChanger) -- link to video
- Learning Data Science Using Functional Python by Joel Grus (Google) -- link to video
- University of Washington eScience Institute (Sponsor Talk) by Jake VanderPlas (University of Washington) -- link to video
- Building a JIT for Python by Dino Viehland (Microsoft) -- link to video
- Democratizing Data Science by Benjamin Mako Hill & Tommy Guy (UW / Microsoft) -- link to video
- Swarm Intelligence Optimization using Python by James McCaffrey (Microsoft) -- link to video
- Jupyter for Education: Beyond Gutenberg and Erasmus by Paco Nathan (O'Reilly) -- link to video
- Counterfactual evaluation of machine learning models by Michael Manapat (Stripe) -- link to video
- Integration with the Vernacular by James Powell (Speaker_Co) -- link to video
- Big Data Analytics - The Best of the Worst : AntiPatterns & Antidotes by Krishna Sankar (blackarrow.tv) -- link to video
- State of the Library: matplotlib by Thomas Caswell (Matplotlib) -- link to video
- Python Data Bikeshed by Rob Story (Simple Finance) -- link to video
- Bot or Not by Erin Shellman (AWS) -- link to video
- Low Friction NLP with Gensim by Trent Hauck (Nyx Labs) -- link to video
- Bokeh Dashboard Capability Use Case/Demo by Casey Clements (Continuum) -- link to video
- The Possibilities Of Plotting With pandas and IPython by Matthew Sundquist -- link to video
- High-Throughput Processing of Space Debris Data by Andreas Schreiber (DLR) -- link to video
- Numba: Flexible analytics written in Python with machine-code speeds and avoiding the GIL. by Travis Oliphant (Continuum) -- link to video
- Jupyter Notebooks and ML Model Operationalization (Sponsor Talk) by Dino Viehland & Raymond Laghaeian (Microsoft) -- link to video
- NLP and text analytics at scale with PySpark and notebooks by Paco Nathan (O'Reilly) -- link to video
- An example of Predictive Analytics: Building a Recommendation Engine using Python by Anusua Trivedi (TACC) -- link to video
- Statistical learning of human brain structure by Ariel Rokem (University of Washington) -- link to video
- Pandas Under The Hood: Peeking behind the scenes of a high performance data analysis library by Jeffrey Tratner (Counsyl) -- link to video
- Bayesian inference with PyMC 3 by John Salvatier (Amazon) -- link to video
- Sequoia: Point Cloud Processing and Meshing by Mark Wiebe (ThinkBox) -- link to video
- Creating an intelligent world at Dato. by Shawn Scully (Dato) -- link to video
- Mistakes I've Made by Cameron Davidson Pilon (Shopify) -- link to video
- Why "data-informed" beats "data-driven. by Greg Reda -- link to video
- Social Media Brand Positioning Workflow by David Gerson (Citigroup) -- link to video
- Top 5 uses of Redis as a Database by Dave Nielsen (Redis Labs) -- link to video
- Machine Learning with Scikit-Learn by Jake VanderPlas(University of Washington) -- link to video
- Python for Data Science: A Rapid On-ramp Primer by Joe McCarthy (Indeed) -- link to video
- Simplified statistics through simulation by Justin Bozonier (Grub Hub) -- link to video
- PySnpTools: A New Open-Source Library for Reading and Manipulating Matrix Data (including Genomics) by Karl Cadie (Microsoft Research) -- link to video
- Scalable Pipelines w/ Luigi or: I’ll have the Data Engineering, hold the Java! by Jonathan Dinu (Galvanize) -- link to video
- Pandas: .head() to .tail() by Tom Augspurger (Mittera) -- link to video
- Beautiful Interactive Visualizations in the Browser with Bokeh by Bryan Van de Ven (Continuum) -- link to video
- A brief introduction to Distributed Computing with PySpark by Holden Karau -- link to video
- Dask: out-of-core arrays with task scheduling by Matthew Rocklin (Continuum) -- link to video
- Using Python for Linguistic Data Analysis by Rutu Mulkar Mehta (Moz) -- link to video
- Learn to Build an App to Find Similar Images using Deep Learning by Piotr Teterwak (Dato) -- link to video
- Real-Time Change Detection on Streaming Data (Sponsor Tutorial) by Cody Rioux (Netflix) -- link to video