Conference Schedule

View past PyData event schedules here.

General Sessions — Saturday Dec. 7, 2019

  Track 1 Track 2 Track 3
8:00 AM

Registration & Breakfast
9:00 AM

Opening Notes
9:10 AM Extending Python Into the Future Travis E Oliphant
9:35 AM What the...? Data Science Questions Asked and Answered Katrina Riehl
10:00 AM

Break
10:15 AM Customizing JupyterLab using extensions Alex Bozarth, Luciano Resende Panel: Dashboards for PyData James A. Bednar Q&A with Keynote Travis Oliphant Travis E Oliphant
11:00 AM Saving Animals with Data: 3 Case Studies in Applying Advanced Technology in Animal Shelters Dr. Kevin Horecka Q&A with Keynote Katrina Riehl Katrina Riehl
11:45 AM Multilingual embeddings to scale NLP models to multiple languages Deeksha Yennam The Cortex in the Code: How Neuroscience Makes AI Intelligent Dalton A. R. Sakthivadivel Addressing the Scarcity of Data Scientist Joe Gartner
12:30 PM

Lunch
1:30 PM Frictionless Data Pipelines Lilly Winfree Objectionable Content James Powell ADTK: An open-source Python toolkit for anomaly detection in time series Tailai Wen
2:15 PM Speeding up Machine Learning tasks using GPUs in Python Saloni Jain Machine Learning Crash Course Samuel Taylor
3:00 PM uarray: Separating interface from implementation Travis E Oliphant Hyperrest: A new Apache Arrow API For High Performance Data Access in Pandas Sudheesh Katkam Recommendations at Rappi: from MVP to Data Product Ariel Wolfmann
3:45 PM

Coffee & Snacks Break
4:00 PM Becoming a Data Head, a reflection on the trade offs and decision points in build a data team Andy Terrel
4:45 PM

Lightning Talks
5:30 PM

Social Event
Hosted by Quansight
8:30 PM

General Sessions — Sunday Dec. 8, 2019

  Track 1 Track 2 Track 3
8:00 AM

Registration & Breakfast
9:00 AM

Opening Notes
9:15 AM Q&A with Peter Wang, CEO and co-founder of Anaconda Peter Wang
10:00 AM

Break
10:15 AM Introducing Dask-Gateway: Dask clusters as a service Jim Crist An Introduction to Sentiment Analysis of Textual Data Fatma Tarlaci, Dhavide Aruliah Values-based OSS Open Discussion Peter Wang
11:00 AM Evaluation of Cloud Hosting Frameworks for Machine Learning Based Equipment Monitoring Pushkar Kumar Jain Develop Data Science for Business Value: a Phoenix Story Morgan Cundiff
11:45 AM AI pipelines powered by Jupyter notebooks Luciano Resende, Alan Chin Accelerate large-scale machine learning with NP on MXNet​ Hao Jin metadsl: separating API from execution Saul Shanabrook
12:30 PM

Lunch
1:30 PM Data Science: How do you even? Julie Hollek
1:55 PM

Break
2:05 PM Working interactively with large and remote datasets in JupyterLab Max Klein, PhD Putting Tensorflow Models into Production Bugra Akyildiz Q&A with Keynote Julie Hollek Julie Hollek
2:50 PM Enhancing Common Natural Language Processing with Cognitive Linguistics Chris Leonard Building a User Maintainable Visualization Dashboard for the Large Synoptic Survey Telescope (LSST) Dharhas Pothina
3:35 PM

Coffee & Snacks Break
3:50 PM Do You Want To Build A Forest? Thomas J Fan Productionalizing a Data Science Team Nicole Carlson Visualizing Machine Learning of Units of Measure using PyViz Jacob Barhak
4:35 PM

Closing Notes
4:45 PM

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