Image Registration: From SIFT to Deep Learning. Useful to know. https://t.co/iL7V7SuQRl
— Nando de Freitas (@NandoDF) July 18, 2019
Image Registration: From SIFT to Deep Learning. Useful to know. https://t.co/iL7V7SuQRl
— Nando de Freitas (@NandoDF) July 18, 2019
The Practice of Reproducible Research: Case Studies and Lessons from the Data-Intensive Sciences https://t.co/nfXqytc6ZD this book is available for free online! I can't wait to read through. #qbioed19
— Amelia McNamara (@AmeliaMN) July 17, 2019
Pushed 3 new chapters to book "The Mechanics of Machine Learning" (by me and @jeremyphoward) https://t.co/kdjaborH6S These chaps detail EDA and model training for bulldozer sales Kaggle competition.
— Terence Parr (@the_antlr_guy) July 16, 2019
Outlier https://t.co/eZ2bbpDzwV pic.twitter.com/qgc8wE1kWf
— Chris Albon (@chrisalbon) July 16, 2019
"match.arg(): a weird function that can help you write better functions" by @alistaire https://t.co/ZrPh5mSMbY #rstats pic.twitter.com/yF7fxG6ksI
— Mara Averick (@dataandme) July 16, 2019
🔪 Great content, and hilarious slides!
— Mara Averick (@dataandme) July 16, 2019
"Get up to speed with Bayesian data analysis in R" by @rabaathhttps://t.co/DDTagwkcr3 #rstats pic.twitter.com/vxz7M7Tdft
See also the forum discussion: https://t.co/NwW9EQWngM
— Jeremy Howard (@jeremyphoward) July 15, 2019
Nice implementations and visual examples of the powerful new CutMix and RICAP augmentation methods, along with cutout and MixUp exampleshttps://t.co/Vy8ghq8zK9 pic.twitter.com/oP0SSYlI7g
— Jeremy Howard (@jeremyphoward) July 15, 2019
New tutorial!🚀 Learn how to perform Video Classification with #Keras and #DeepLearning 📽️📺
— Adrian Rosebrock (@PyImageSearch) July 15, 2019
Full tutorial, including #Python code w/ pre-trained model, can be found here: https://t.co/idY0mqotxq 👍#MachineLearning #ComputerVision #ArtificialIntelligence #AI #DataScience pic.twitter.com/yfSoHZRn2v
Great summary of the "Information Theory" essentials by @SimonDeDeo featuring all the good stuff like Kullback-Leibler divergence, mutual information, Jensen-Shannon Distance, etc. :) https://t.co/uydSgnxfS5 https://t.co/L37nXgW1Rl
— Sebastian Raschka (@rasbt) July 12, 2019
Code from my lightning talk: ensemble topic modelling in Python with pLSA for fast stable topic modelling with the enstop package: https://t.co/fXTHqwbWIu #SciPy2019
— Leland McInnes (@leland_mcinnes) July 12, 2019
Really great keynote by @math_rachel on recent developments in NLP and ML, the principles of transfer learning and the dangers of algorithms that create realistic prose and videos https://t.co/RzzsXD5V9s
— Andreas Mueller (@amuellerml) July 12, 2019