So many things you can do with #Jupyter notebooks, including:
— PyData (@PyData) February 16, 2019
"Extending Jupyter with Google Cloud Storage file system backend" by Egor Bulychev—work with notebooks & other files directly in Google Cloud Storage:https://t.co/sWOOXsyLNI
Subscribe to #PyData on Youtube for more!
Really enjoyed my conversation with @reidhoffman onstage at @StartupGrind today, talking about OpenAI and the shape of AGI progress: https://t.co/XQ2ljx2ASe
— Greg Brockman (@gdb) February 14, 2019
So much to learn about #machinelearning & #artificialintelligence on #pydata videos, including:
— PyData (@PyData) February 12, 2019
"Data versioning in machine learning projects" by Dmitry Petrov — how to solve the issue of discrepancy between code & data files https://t.co/4B317wMMnq
Don't forget to subscribe!
A lecture on security and privacy in ML I recently gave is now available on YouTube. It covers a bunch of open problems in this space. Thanks for @jacobsteinhardt @smnh_azadi @dawnsongtweets @trevor_darrell_ for inviting me
— Nicolas Papernot (@NicolasPapernot) February 12, 2019
@UCBerkeley
Video: https://t.co/5zbfpmcxMx
Lots of #dataviz talks on our #pydata video playlist, including:
— PyData (@PyData) February 11, 2019
"Data Science & Data Visualization in Python" by Radovan Kavickyhttps://t.co/vafLdmuRmD#datavisualisation #datanalysis #python
Don't forget to subscribe to the #PyData channel!
Get to know #pandas on our video playlist, including:
— PyData (@PyData) February 10, 2019
"Towards Pandas 1.0" by Marc Garcia - covering pandas' past, latest features, and what to expect from the project in the futurehttps://t.co/9iRuBuAXeH
Subscribe to the #PyData Youtube channel for more great #python talks!
The livestream 📺 for the #H2OWorld H2O-3 & #AutoML hands-on training is happening now! https://t.co/dlWshrZxLB
— Erin LeDell (@ledell) February 4, 2019
NLP demo: https://t.co/724AvZvyuS
AutoML demo: https://t.co/LzEUAgNzXO
So much to learn about #machinelearning & #artificialintelligence on #pydata videos, including:
— PyData (@PyData) February 4, 2019
"Data versioning in machine learning projects" by Dmitry Petrov — how to solve the issue of discrepancy between code & data files https://t.co/4B317wMMnq
Don't forget to subscribe!
Great demonstration of what I recommend to beginners: collect your own data (or download a dataset) on a topic that matters to you, and do an analysis project on it that can be added to your portfolio! https://t.co/LU3um41ChE
— Data Science Renee (@BecomingDataSci) February 3, 2019
BRRR-ooke's #rstatsnyc talk is 🔥 every time!
— Mara Averick (@dataandme) February 3, 2019
"Open Source Sampling: building and remixing 📦s in R" 👩🎤 @brookLYNevery1
📽 https://t.co/sKx75Zs5zN
🎥 https://t.co/k5xKD9D1Dm#rstats pic.twitter.com/HbcKgjgocZ
Interesting presentation: #Netflix software engineers discuss the technical challenges of developing the UI & playback system for the #BlackMirror: #Bandersnatch interactive film. #programming #JavaScripthttps://t.co/prj3QUBW4O
— Randy Olson (@randal_olson) February 2, 2019
Curious about #julialang? Learn more on our #PyData video playlist, including:
— PyData (@PyData) February 1, 2019
"Introduction to Julia for Scientific Computing and Data Science" by David Higgins & Robert Schwarz - an intro to the language and sampling of packageshttps://t.co/NEFxD9DGCf
Remember to subscribe!
