👍 code-through w/ nice viz, too!
— Mara Averick (@dataandme) March 25, 2019
"awtools Update: Visualizing Natural Disaster Cost" 👨💻 @awhstinhttps://t.co/daJD2DLZur #rstats #dataviz pic.twitter.com/sTwWKECjTX
👍 code-through w/ nice viz, too!
— Mara Averick (@dataandme) March 25, 2019
"awtools Update: Visualizing Natural Disaster Cost" 👨💻 @awhstinhttps://t.co/daJD2DLZur #rstats #dataviz pic.twitter.com/sTwWKECjTX
🐦 Wanna use twitter data like a pro? (slides & code)
— Mara Averick (@dataandme) March 24, 2019
📽 "rtweet workshop: Collecting and analyzing Twitter data" by @kearneymw https://t.co/d4jdq7EkdN #rstats #ddj pic.twitter.com/H3dlolJ6cS
Just finished rewriting the ConvNet chapter! 😅
— Aurélien Geron (@aureliengeron) March 24, 2019
Now includes building ResNet-34 in #TensorFlow 2 (see image), fine-tuning a pretrained model, object detection and image segmentation.
I pushed the notebook: https://t.co/YEkeSzGT1V pic.twitter.com/eNt0YhxqIf
Keras in TensorFlow 2.0 has a new developer guide, with lots of useful content for power users: https://t.co/Dzrl15ftto
— François Chollet (@fchollet) March 22, 2019
😻 Feat. deploy previews…
— Mara Averick (@dataandme) March 18, 2019
"A Blogdown New Post Workflow w/ Github and Netlify" 👨💻 @grrrck https://t.co/tUSjuStjLB #rstats #rmarkdown
🏀 Ready for some bRacketology? @samfirke's got you covered:
— Mara Averick (@dataandme) March 18, 2019
⛹️♂️ "Making March Madness predictions - a how-to guide"https://t.co/UAc6sgIOW9 #rstats #MarchMadness pic.twitter.com/qyrN4iUGT8
Holistically-Nested Edge Detection with OpenCV and Deep Learning via @pyimagesearch https://t.co/VeRbri5Jnw #python #opencv #deeplearning pic.twitter.com/dFP6dIY3hz
— Python Weekly (@PythonWeekly) March 12, 2019
👍 From basic data exploration to K-means and UMAP…
— Mara Averick (@dataandme) March 11, 2019
💊 "Clustering the Pharmaceutical Industry Stocks" by @htoscano84 https://t.co/rvS8Bfdl8z #rstats pic.twitter.com/RRD7pbJSIb
Everything you need to know about porting your TensorFlow 1.x code to @TensorFlow 2.0, from Tomer and Anna.
— 👩💻 DynamicWebPaige (@DynamicWebPaige) March 7, 2019
👇In-depth guides can be found here:
https://t.co/7OaQG5xTVmhttps://t.co/eTBSLbVySn#TFDevSummit
Send questions to #AskTensorFlow! We'll be answering on YouTube soon. pic.twitter.com/9GvEczt89p
💯 “Despite its prevalence, censored time-to-event data is often overlooked, leading to dramatically biased predictions.” https://t.co/C8uvtPC6OM
— Erik Bernhardsson (@fulhack) March 2, 2019
Classification / metric learning using @fastdotai!
— Radek Osmulski (@radekosmulski) March 1, 2019
The notebook features:
✅custom loss (combination of cross entropy and contrastive loss)
✅sampling progressively harder datasets
✅all the @fastdotai goodies (discriminative lrs, one cycle)https://t.co/bicTSuTU8x pic.twitter.com/kAdijrUUCy
TPUs in Google Colaboratory, now with less boilerplate code. See the Keras TPU sample here: https://t.co/RIpkluc09d
— Martin Görner (@martin_gorner) February 13, 2019
google.colab.auth.authenticate_user() to propagate your credentials to the backend and the TPU. TPUClusterResolver() to find your TPU. That's it!