39:32
Keynote - Kelly Jin: A Few Good Public Servants: How Great Analysis Inspires Action | PyData NYC 19
PyData
38:08
Keynote - Chris Wiggins, Anne Bauer: Data science at The New York Times | PyData NYC 2019
44:42
Keynote - Sara Seager: Stars, Planets, and Python | PyData NYC 2019
1:20:44
Marc Garcia, Jeff Reback, Tom Augspurger: Introduction to pandas | PyData New York City 2019
1:29:48
Raoul-Gabriel Urma: Advanced Software Testing for Data Scientists | PyData New York 2019
1:30:48
Sumowska, Desikan, Warner, Konstantinovskiy: Role playing Annotation workshop | PyData New York 2019
1:32:12
Matti Lyra: Neural Networks for Natural Language Processing | PyData New York 2019
1:23:30
Aditi Khullar, Eugene Tang: Introduction to Language Modeling | PyData New York 2019
1:13:45
Mariel Frank: Introduction to NLP | PyData New York 2019
1:20:25
Mitzi Morris: Bayesian Inference for Fun and Profit | PyData New York 2019
1:25:46
Cameron Davidson-Pilon: New Trends in Estimation and Inference | PyData New York 2019
1:18:27
Hillary Green-Lerman, Michoel Snow: A/B Testing with SciPy | PyData New York 2019
1:30:12
Will Kurt: An Introduction to Probability and Statistics | PyData New York 2019
1:33:04
Stanley van der Merwe, Petr Wolf: From Raw Recruit Scripts to Perfect Python | PyData New York 2019
1:23:40
Carlos Afonso: Visualizing the 2019 Measles Outbreak in NYC (with Python) | PyData New York 2019
1:30:10
Chris Fonnesbeck: A Primer on Gaussian Processes for Regression Analysis | PyData NYC 2019
1:21:43
Keith Kraus: High-Performance Data Science at Scale with RAPIDS, Dask, and GPUs | PyData NYC 2019
1:28:03
Michoel Snow, Hillary Green-Lerman: Hacking the Data Science Challenge | PyData New York City 2019
32:20
Allen Downey: The Inspection Paradox is Everywhere | PyData New York 2019
40:25
Julia Signell: Data-centric exploration using intake, dask, hvplot, and more | PyData New York 2019
32:36
Malaika Handa: Colorism in High Fashion (featuring: K-Means Clustering) | PyData New York 2019
38:56
Akos Furton: Production Code in Data Science Consulting | PyData New York 2019
43:03
Francesc Alted, Christian Steiner: Improve the efficiency of your Big Data.. | PyData New York 2019
42:32
Noam Ross: Building Software and Communities With Peer Review | PyData New York 2019
35:12
Kamal Abdelrahman: Painting a Picture of Public Data | PyData New York 2019
39:30
Tamar Yastrab: The Echo-Chamber of Your Social Media Feed | PyData New York 2019
28:38
Ferras Hamad: Reproducibility in ML Systems: A Netflix Original | PyData New York 2019
32:54
Steve Dower: The Secret Life of Python | PyData New York 2019
37:59
Colin Carroll, Hannah Aizenman, Thomas Caswell: Building a maintainable plotting library-PyData NYC
30:09
Raphaël Meudec: tf-explain: Interpretability for Tensorflow 2.0 | PyData New York 2019
43:55
Moussa Taifi: Clean Machine Learning Code: Practical Software Engineering... | PyData New York 2019
34:35
Romain Cledat: Every ML Model Deserves To Be A Full Micro-service | PyData New York 2019
32:13
Thomas J Fan: Deep Dive into scikit-learn's HistGradientBoosting Classifier.. | PyData New York 2019
18:51
James Powell: Sloth & ENVy | PyData New York 2019
32:33
Maciej Wojton: Free Your Esoteric Data Using Apache Arrow and Python | PyData New York 2019
23:20
Ian Whalen: Implementing Lightweight Random Indexing for Polylingual Text Classification -PyData NYC
39:43
Martin Hirzel: Type-Driven Automated Learning with Lale | PyData New York 2019
39:24
Alex Egg, Emily A Ray, Parin Choganwala: Discover your latent food graph with this 1... | PyData NYC
31:03
Aditya Lahiri: Dealing With Imbalanced Classes in Machine Learning | PyData New York 2019
31:56
Kelly Shen: Julia for Pythonistas | PyData New York 2019
52:15
Joe Jevnik: Zarr vs. HDF5 | PyData New York 2019
34:32
Jessica Tyler: Geo Experiments and Causal Impact in Incrementality Testing | PyData New York 2019
34:29
Jacqueline Gutman: Simplified Data Quality Monitoring of Dynamic Longitudinal.. | PyData NYC 2019
22:52
Chaya D Stern, Yuanqing Wang: Using Graph Nets (GNs) to predict molecular properties | PyData NYC
35:08
Daniel Rodriguez: Effective Python and R collaboration | PyData New York 2019
39:14
Anthony Scopatz: Conda-press, or Reinventing the Wheel | PyData New York 2019
40:55
Veronica Hanus: To comment or not | PyData New York 2019
37:17
Jenny Turner-Trauring: Working with Maps: Extracting Features for Traffic Crash... | PyData NYC 2019
Bill Lynch: Bringing mental health data to doctors | PyData New York 2019
32:43
Samuel Rochette: Quantifying uncertainty in machine learning models | PyData New York 2019
34:01
Eric Dill: Is Spark still relevant? Multi-node CPU and single-node GPU workloads.. | PyData NYC 2019
38:28
Tom Augspurger: Scalable Machine Learning with Dask | PyData New York 2019
33:47
Amanda Moran: Pandas vs Koalas: The Ultimate Showdown! | PyData New York 2019
34:18
Ethan Rosenthal: Time series for scikit-learn people | PyData New York 2019
35:07
Evan Patterson: Semantic modeling of data science code | PyData New York 2019
30:54
Katherine Kampf: Build an AI-powered Pet Detector in Visual Studio Code | PyData New York 2019
36:13
Joshua Falk: Generating realistic, differentially private data sets using GANs | PyData NYC 2019
26:14
Saul Shanabrook: Same API, Different Execution | PyData New York 2019
34:26
Michael Johns: Propensity Score Matching: A Non-experimental Approach to Causal... | PyData NYC 2019
38:30
Diego Torres Quintanilla: Cleaning, optimizing and windowing pandas with numba | PyData NYC 2019
34:06
Itamar Turner-Trauring: Small Big Data: using NumPy and Pandas when your data... | PyData NYC 2019
35:11
Patrick Landreman: A Crash Course in Applied Linear Algebra | PyData New York 2019
32:42
Lauren Oldja: Managing Stakeholders: The Key to Successful Data Science for Business | PyData NYC
36:49
Li Jin, Hyonjee Joo: Spark Backend for Ibis: Seamless Transition Between Pandas... | PyData NYC 2019
33:29
Meghan Heintz: Launching a new warehouse with SimPy at Rent the Runway | PyData New York City 2019
Marianne Hoogeveen: The physics of deep learning using tensor networks | PyData New York City 2019
35:22
Jens Fredrik Skogstrom: What we learned by running a large custom Bayesian... | PyData NYC 2019
37:43
Marius van Niekerk, Rohit Kapur: A How-to guide for migrating legacy data applications | PyData NYC
35:54
Piero Ferrante: Should I develop my own DS library? Maybe. | PyData New York City 2019
