ssh tips pic.twitter.com/iLvKv1vdZg
— 🔎Julia Evans🔍 (@b0rk) January 23, 2019
ssh tips pic.twitter.com/iLvKv1vdZg
— 🔎Julia Evans🔍 (@b0rk) January 23, 2019
Slides for my talk: https://t.co/yVfM63MZ6v [pdf]
— Data Science Renee (@BecomingDataSci) January 23, 2019
longer version with notes and links: https://t.co/jpD5MVvqfk [pdf]
Here are the slides and the links to additional resources (like super chickens! 🦸♀️🐓) https://t.co/HiB2cioVXL
— Angela Bassa (@AngeBassa) January 20, 2019
Interested in statistical methods for data science? Check out our probabilistic programming and bayesian methods playlist, including:
— PyData (@PyData) January 20, 2019
"Bayesian Network Modeling using R and Python" by Pragyansmita Nayak: https://t.co/CNw92p8jAJ
Don't forget to subscribe to #PyData on Youtube!
Here is my write-up on #RStudioConf! I saw three big topics:
— Jacqueline Nolis (@skyetetra) January 20, 2019
💍 Shiny is a Serious Deal
🖥 R is used in Production
💼 Data Science Skills Matterhttps://t.co/QqKII9MJWm
Using Feedparser, Difflib and Plotly to Analyze Blog Tags https://t.co/jGDVw2wCKr
— PyCoder’s Weekly (@pycoders) January 19, 2019
Understanding Convolutional Neural Networks through Visualizations in PyTorch by Vihar Kurama https://t.co/wLlA2AlZnY #pytorch #deeplearning #machinelearning #ml #ai #neuralnetworks #datascience
— PyTorch Best Practices (@PyTorchPractice) January 19, 2019
The Random In Random Forest https://t.co/eZ2bbpDzwV pic.twitter.com/41IxkO3Fr0
— Chris Albon (@chrisalbon) January 18, 2019
📽 Check out @earowang's slides from her stellar talk at #rstudioconf:
— Mara Averick (@dataandme) January 18, 2019
⏰ "Melt the clock: tidy time series analysis"https://t.co/5xkkMpAsxn #rstats #timeseries pic.twitter.com/obRUArdmAC
it depends: a dialog about dependencies
— Jim Hester (@jimhester_) January 18, 2019
Slides from my #rstudioconf talk at https://t.co/7uUF1H0drK
A follow-up to my introduction to causal inference and do-calculus. This is based on my lectures at MLSS Africa last week. I'm turning that material into a series of posts, stay tuned.
— Ferenc Huszár🇪🇺 (@fhuszar) January 18, 2019
Causal Inference 2: Illustrating Interventions via a Toy Examplehttps://t.co/kz79zYaX0Q
This is extremely cool Mudano, a project management company, shows how to use fastai's pretrained NLP @pytorch language model and transfer learning to rapidly build a classifier for project status reports.
— Jeremy Howard (@jeremyphoward) January 18, 2019
Really nice end-to-end walkthru of full model training process. https://t.co/lMbURQk7tc