New blog entry!💫 In no particular order, here are the coolest things I learned at #JupyterCon: https://t.co/XRBifSElxw #DSLearnings
— Caitlin Hudon👩🏼💻 (@beeonaposy) August 27, 2018
New blog entry!💫 In no particular order, here are the coolest things I learned at #JupyterCon: https://t.co/XRBifSElxw #DSLearnings
— Caitlin Hudon👩🏼💻 (@beeonaposy) August 27, 2018
Check out our intelligent @Slack bot named Mr. Jingles! Our office mascot, once a humble cat, can now fetch stories, create visualizations, and even explain spikes in news coverage :smiley_cat: #mediamonitoring #chatbots https://t.co/HcZRIX13G7 pic.twitter.com/lsZ98oRU23
— AYLIEN (@_aylien) August 27, 2018
For anyone who has ever thought - "Can I learn the math needed for Deep Learning all in one place (and maybe skip the other stuff)?" - this is quite a nice resource.
— Trask (@iamtrask) August 27, 2018
"The Matrix Calculus You Need For Deep Learning"https://t.co/L1YQ9IVZ16
(Table of Contents Below) pic.twitter.com/b4ETNBbO24
🎉 Video from #rstatsnyc is up!
— Mara Averick (@dataandme) August 26, 2018
😹 So much amazing!
📺 "New York R Conference: 2018"https://t.co/DgRQjcpIrz #rstats pic.twitter.com/C4o0mcUVoC
💕 In the absence of video, you should at least see @jaredlander's #rstatsnyc slides! Hilarious and on point. 💥
— Mara Averick (@dataandme) August 26, 2018
📽 "Deep Learning vs Machine Learning in R" https://t.co/P544zbD8mD #rstats #keras
/* 🖍 malarkey mine */ pic.twitter.com/h26ebfkAg7
Understanding Python Dataclasses — Part 1 – https://t.co/4gBBXtlbfe
— Pycoders Weekly (@pycoders) August 25, 2018
The State of AI/ML in Python (including brief histories of SciPy and NumPy) @teoliphant slides from @py_bay keynotehttps://t.co/HYzKjhATB0
— Rachel Thomas (@math_rachel) August 25, 2018
Self-starter Guide to Becoming a #DataScientist: https://t.co/plV2ebkc9T #BigData #AI #Careers #DataLiteracy #Coding
— Kirk Borne (@KirkDBorne) August 24, 2018
Includes:
🔘Free #DataScience Study Resources for Beginners
🔘Data Science Primer
🔘Overview of Modern #MachineLearning #Algorithms
🔘Fun Projects for Beginners pic.twitter.com/BFuDZC6AAB
Affective computing aims to model how emotion impacts decision-making. @lmoroney talks with Christian Ramsey about using TensorFlow to model complex, emotional behavior and adding the affective layer to deep learning.
— TensorFlow (@TensorFlow) August 23, 2018
Watch #TensorFlowMeets here → https://t.co/IQ1JDIAaIv pic.twitter.com/BaZI5DibF8
h/t @WalterReade for this informative video ft. Marc Garcia at #PyData. Most interesting, he says, are the efforts to make pandas scale better, and the future deprecation of `inplace=True`https://t.co/jp5fjb3JJl
— Kaggle (@kaggle) August 23, 2018
Continuously impressed by @distillpub publications. This one on feature transformation does such a good job of centralizing and explaining trends around multimodal learning. An informative read that will leave you wanting to try out a lot of ideas. https://t.co/W890jMEyxB
— Emmanuel Ameisen (@EmmanuelAmeisen) August 23, 2018
I just crunched the numbers and determined I make (on average) $1.86 on each copy of R4DS — so you should never feel about using the free website! (https://t.co/48IKOWCtSc)
— Hadley Wickham (@hadleywickham) August 22, 2018