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Event: PyData LA 2018
Other events in this series:
2018
2019
Building a Visualizer in Yellowbrick
Building an Open Platform for Sustaining Data Science Innovation: A Tour of NumFOCUS Projects
Customer Lifetime Value: Models, Metrics and a Multitude of Uses
Deploy and Use a Multiframework Distributed Deep Learning Platform on Kubernetes
Extending Pandas with Custom Types
Keynote #4: What is a Data Desk?
Keynote #5: The New Science of Cause and Effect
Measuring Model Fairness
Python at City Scale
StaticFrame: An Immutable Alternative to Pandas
Train, Evaluate, Repeat: Building a Credit Card Fraud Detection System
Using Data to Get Your Next Raise
Using Simpson’s Paradox to Discover Interesting Patterns in Behavioral Data
What's the Science in Data Science?
1D Convolutional Neural Networks for Time Series Modeling
Accelerating Data Science with RAPIDS
Attacking Clustered Data with a Mixed Effects Random Forests Model in Python
Data Mining JIRA Tickets to Gain Insights into Organizational Behavior
(Deep) Learn You a Neural Net for Great Good!
Detecting Signed and Unsigned Documents with Deep Learning - Beyond Transfer Learning
Developing Dashboard Applications Using Bokeh
Extracting Structured Data from Legal Documents
Help! I Just Inherited 50,000 Lines of Code! What Do I Do? — A Practical Guide
Hot Water Leak Detection Using Variational Autoencoder Model
Iodide and Pyodide: Bringing Data Science Computation to the Web Browser
JupyterLab: The Evolution of the Jupyter Notebook
Keynote #1: Building a Player-Focused Data Team at Riot Games
Keynote #2 - Tensorly: A Flexible Python Framework for Machine Learning
Serverless for Data Scientists
Time, Interrupted: Measuring Intervention Effects with Interrupted Time-Series Analysis
Why You Should Do Text Analysis in Python (Even if You Don't Want to)
An Introduction to Julia
Applying Statistical Modeling and Machine Learning to Perform Time-Series Forecasting
CatBoost - The New Generation of Gradient Boosting
Docker for Data Science: Reproducibility and Deployment
Introduction to Data Manipulation and Visualizations in R
Learning to Scale Data Science, Machine Learning, and Pandas with Ray and Modin
Making Computation Easier with Cool Numpy Tricks
Network Science, Game of Thrones and US Airports
Testing with Pytest for Data Science
Tips, Tricks and Topics in Text Analysis
When Rotten Tomatoes Isn’t Enough: Analyzing Twitter Movie Reviews Using DataStax Enterprise