📈 Great start-to-finish tutorial by @zabormetrics…
— Mara Averick (@dataandme) June 13, 2019
👩🏫 "Survival Analysis in R" https://t.co/LqmsYXF2FW #rstats pic.twitter.com/9ADVnYmqSf
📈 Great start-to-finish tutorial by @zabormetrics…
— Mara Averick (@dataandme) June 13, 2019
👩🏫 "Survival Analysis in R" https://t.co/LqmsYXF2FW #rstats pic.twitter.com/9ADVnYmqSf
Two more chapters available in the early release! https://t.co/zOTk6cOUjW
— Aurélien Geron (@aureliengeron) June 12, 2019
* 16: Processing sequences (eg. time series) using RNNs (eg. LSTM, GRU) and CNNs (eg. Wavenet).
* 17: Natural Language Processing using RNNs (Encoder-Decoder) and Attention models (Transformer).
Enjoy! 🦎
Generative Adversarial Networks: A Survey and Taxonomy
— ML Review (@ml_review) June 11, 2019
By @wangvilla @sheqi1991 @tomasward
Covering 7 architecture-variant GANs and 9 loss-variant GANs focusing on
(1) High quality image generation
(2) Diverse image generation
(3) Stable training https://t.co/tI9o6Xepr4 pic.twitter.com/Mx6SRCgtzv
We've compiled a meta-reading list for our meta-learning tutorial: https://t.co/3i5zohN4KM
— Sergey Levine (@svlevine) June 11, 2019
Short list of the main papers we covered in our meta-learning tutorial:https://t.co/g3eAcsO0vr https://t.co/TdWZNyn9kB
Great list of resources on the syllabus for Ethics in NLP course @emilymbender @UW https://t.co/gg9aZBWvDN pic.twitter.com/6QnU1myCAJ
— Rachel Thomas (@math_rachel) June 10, 2019
Read @lavanyaai's awesome Kernel detailing how she climbed the competition leaderboard | "How I made top 0.3% on Kaggle" 👉📈 https://t.co/e0hQhOtAW1
— Kaggle (@kaggle) June 10, 2019
Hi all. I’ve posted my slides from my talk today https://t.co/mbl6kpfocm
— Mark Riedl 🚀 Mars (Moon) (@mark_riedl) June 8, 2019
Topics covered: (1) the potential benefits of narrative AI systems, (2) historical perspectives on story generation, (3) machine learning for story generation, (4) controlling neural text generation systems https://t.co/o7zx5OOd5N
This @waitbutwhy breakdown is game theory at its most entertaining!
— Mara Averick (@dataandme) June 7, 2019
"Did James make the right Final Jeopardy bet?" https://t.co/uuSpkCGXpu pic.twitter.com/dXa7kcJWg3
Eigenvector https://t.co/eZ2bbpDzwV pic.twitter.com/QuJvnwHU2k
— Chris Albon (@chrisalbon) June 7, 2019
Some slides I threw together for an "Explainable AI" meetup last night. Let's call the talk about some combination of data ethics, explainability, and ML engineering best practices.
— Joel Grus ♥️ 📓 (@joelgrus) June 7, 2019
"You have 34 slides!"
"That's right"
"It's a 10 minute talk!"
"👍"https://t.co/kP13NNqCwa
Videos from last week’s workshop on Learning for Dynamics and Control are now online! #L4DC https://t.co/x0DmcWtGTk
— Ben Recht (@beenwrekt) June 7, 2019
Interested in Machine Learning? Check out this talk "End to End Machine learning Pipelines for Python Driven Organizations" from PyData DC #MLhttps://t.co/Jq9n5g6za2
— PyData (@PyData) June 7, 2019
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