Task Queues: A Celery Story by Tom Mandersonhttps://pyvideo.org/pycon-au-2018/task-queues-a-celery-story.html. In this talk, you'll learn about why you might want a task queue (and when you definitely don't), when Celery is appropriate, and what you can do when it's not.
— Python Software (@ThePSF) September 15, 2018
Super excited to share my new #rstats @DataCamp course, Categorical Data in the Tidyverse. Learn all about how the forcats 📦, w/ friends ggplot2, stringr, tidyr, & dplyr, can help you effectively wrangle, tame, & visualize your data.https://t.co/KC2aT94cpk pic.twitter.com/1ifCtJgOzq
— Emily Robinson (@robinson_es) September 13, 2018
Two #Statistics articles for #DataScientists:
— Kirk Borne (@KirkDBorne) September 13, 2018
1) Statistical Tests — When to use Which? https://t.co/P8Qd25pEZI
2) Understanding Type I and Type II Errors: https://t.co/6JjlCWfwf0 by @schmarzo #abdsc #BigData #DataScience #Statistics #StatisticalLiteracy #DataLiteracy pic.twitter.com/M4JXCr4Ghi
We've updated our online examples to use Dask's new JupyterLab extension.
— Dask (@dask_dev) September 10, 2018
If you want to try out Dask and JupyterLab together, go here:https://t.co/TRjq7gXKbA
🎓 oh the things you can do with Rmd…
— Mara Averick (@dataandme) September 6, 2018
"Reproducible academic writing w/ RMarkdown" 🗣 @sauer_sebastian https://t.co/g6H3w3yVOr #rstats #rmarkdown pic.twitter.com/uQoXa9dtyd
Check out this helpful walkthrough of Multi-GPU training with Custom Estimators by @krasul .
— TensorFlow (@TensorFlow) September 5, 2018
Read it here ↓ https://t.co/SvVZbO3xbB
ICYMI, 📈 chart explanation on point!
— Mara Averick (@dataandme) September 2, 2018
"Exploring ggplot2 boxplots - Defining limits and adjusting style" 👩💻 @DeCiccoDonkhttps://t.co/Jx3DfOwUy0 via @USGS_R #rstats #dataviz pic.twitter.com/L1U8K99lOo
Scipy lecture notes new release: an open online book (also in PDF) on the scientific and data ecosystem in Pythonhttps://t.co/tAJoR0iycr
— Gael Varoquaux (@GaelVaroquaux) September 1, 2018
Minor update, mostly fixing links, typos, and adding support for new package versions#pydata #scipy pic.twitter.com/8jNZ6n2VSh
This week's #KernelAwards winner uses Local Interpretable Model-Agnostic Explanations (LIME) to better understand the predictions of an ML model: https://t.co/FSvY4WtYqp pic.twitter.com/AdQIMzKX9h
— Kaggle (@kaggle) August 31, 2018
If you've wondered - "Which Deep Learning optimizer should I use? SGD? Adagrad? RMSProp?" - this blogpost by @seb_ruder is the best explanation I've seen.
— Trask (@iamtrask) August 31, 2018
It's a surprisingly easy read! https://t.co/ASebqI7N4J
Definitely a good #100DaysOfMLCode project. pic.twitter.com/wrQ1aLVSvT
🗺-tile-grid made easy w/ this code-through…
— Mara Averick (@dataandme) August 30, 2018
"Simplifying World Tile Grid Creation w/ geom_wtg()" ⚓︎ @hrbrmstrhttps://t.co/7b3pBCNvzp #rstats #dataviz #maps pic.twitter.com/9Oe37m2y8j
Detecting and Outlining Lakes with Python3 and OpenCV 3 – https://t.co/g90H9MqXCu
— Pycoders Weekly (@pycoders) August 29, 2018
