San Francisco, CA
August 2018
pybay.com
Influential speakers presenting on Python topics such as internals, data, performance, devops, and web tech.
Schedule |
Speakers |
Blog
* Deprecating the state machine: building conversational AI with the Rasa stack by Alan Nichol Robots, biology and unsupervised model selection by Amelia Taylor * Detecting business chains at scale with PySpark and machine learning by Andrew Danks * Automated responses to questions about your health by Austin Powell * Reproducible performance by profiling all the code, all the time, for free by Bartosz Wróblewski An import loop and a fiery reentry by Brandon Rhodes * An absolute beginner's guide to deep learning with Keras by Dr. Brian Spiering Diving into production issues at scale by Brian Weber * Using JupyterLab with JupyterHub and Binder by Carol Willing
Machine learning at Twitter: Twitter meets Tensorflow by Cibele Montez
Bootstrapping a visual search engine by Cung Tran * Airflow on Kubernetes: dynamically scaling Python-based DAG workflows by Daniel Imberman, Seth Edwards * Ask Alexa: how do I create my first Alexa skill? by Darlene Wong & Varang Amin Finding Your Place in SRE and SRE in Your Place by David Blank-Edelman Using Keras & Numpy to detect voice disorders by Deborah Hanus How I learned to stop shell scripting and love the StdLib by Elaine Yeung * How to read Python you didn’t write by Erin Allard Modern C extensions: why, how, and the future by Ethan Smith * Tools to manage large Python codebases by Fabio Fleitas 1 + 1 = 1 or record deduplication with Python by Flávio Juvenal * Clearer code at scale: static types at Zulip and Dropbox by Greg Price Docker for data scientists: simplify your workflow and avoid pitfalls by Jeff Fischer * High-performance Python microservice communication by Joe Cabrera Zebras and lasers: a crash course on barcodes with Python by Jonas Neubert First steps to transition from SQL to pandas by Kasia Rachuta 2FA, WTF? by Kelley Robinson * Finding vulnerabilities for free: the magic of static analysis by Kevin Hock * Python services at scale by Lisa Roach Parse NBA statistics with Openpyxl by Lizzie Siegle * Pull requests: merging good practices into your project by Luca Bezerra * Amusing algorithms by Max Humber * Production-ready Python applications by Michael Kehoe * Serverless for data scientists by Mike Lee Williams * Let robots nitpick instead of humans by Moshe Zadka * Deploying Python3 application to Kubernetes using Envoy by Natalie Serebryakova * How to make a multi-tenant microservice by Navin Kumar Building Google Assistant apps with Python by Paul Bailey Data science on geospatial data and climate change by Paige Bailey * Building an AI-powered Twitter bot that guesses locations of pictures from pixels by Randall Hunt * Why you need to know the internals of list and tuple by Ravi Chityala Django Channels and websockets in production! by Rudy Mutter * Beyond accuracy: interpretability in “black-box” model settings by Sara Hooker How to instantly publish data to the internet with Datasette by Simon Willison * Recent advances in deep learning and Tensorflow by Sourabh Bajaj * Service testing with Apache Airflow by Zhangyuan Hu * From batching to streaming: a challenging migration tale by Srivatsan Sridharan * The bots are coming! Writing chatbots with Python by Wesley Chun * asyncio: what’s next by Yury Selivanov