Optimize runtime memory 🏃♀️🧠
— TensorFlow (@TensorFlow) October 2, 2020
In this blog, you’ll learn how TensorFlow Lite optimizes its memory footprint for neural net inference on resource-constrained devices.
Start optimizing → https://t.co/H7AxFTd8Py pic.twitter.com/JQWPIa18uQ
Just stumbled upon the recent "Principles and Practice of Explainable Machine Learning" survey by Vaishak Belle & Ioannis Papantonis, https://t.co/enyjkeSp8W. Looks like a good companion paper for @ChristophMolnar 's interpretable ML book. That's a really useful mindmap: pic.twitter.com/NF0rMlyurU
— Sebastian Raschka (@rasbt) October 2, 2020
I hope you'll enjoy this step-by-step #notebook tutorial
— Andrew Trask (@iamtrask) September 30, 2020
Goal: to be the *easiest* intro to #privacy preserving Deep Learning available
It's in @PyTorch teaching the #PySyft PPML framework
I hope you enjoy it#GDPR #100DaysOfMLCode #100DaysOfCodehttps://t.co/zUORRBt8aS pic.twitter.com/a4tADBc9B1
Want to learn how to use TensorFlow to create TFRecords for Tensor Processing Units? Check out this notebook walkthrough from Kaggle AI Educator @ryanpholbrook! [WATCH] https://t.co/PEPU5ea5as pic.twitter.com/jXdjukGotZ
— Kaggle (@kaggle) September 29, 2020
An overview of the the Machine Learning Infrastructure at Netflix. Genre prediction, Screenplay Analysis, CDN caching, and more. https://t.co/IFPITaO9Vf pic.twitter.com/hYYf1UH2n8
— Reza Zadeh (@Reza_Zadeh) September 29, 2020
The final lecture from our Deep Learning course of last semester is up. https://t.co/6ZKScjwKT6
— Yann LeCun (@ylecun) September 29, 2020
I wrote a short tutorial explaining three different methods for training self-play agents (tournament-style genetic algorithms, self-play PPO, and self-play via cooperation) using Slime Volleyball Gym as an example environment.https://t.co/7rxqW0vLnb https://t.co/j0HWLQuWza pic.twitter.com/L7zVFjN2wx
— hardmaru (@hardmaru) September 24, 2020
T-Statistic https://t.co/eZ2bbpDzwV pic.twitter.com/iBnZEITiXa
— Chris Albon (@chrisalbon) September 23, 2020
Whether you're a football/soccer fan or not, this is a great walk-through of basic class construction, validation, etc…
— Mara Averick (@dataandme) September 23, 2020
⚽️ “S3 Classes and {vctrs} to Create a Soccer Pitch Control Model” by @TonyElHabr https://t.co/6VIEno8n3l #rstats
Let's be real, building neural networks can be an extremely frustrating and painful experience. 🤷♀️🤷♂️
— Hugging Face (@huggingface) September 22, 2020
We have gathered a few tips from our own experience of simple steps you can take when you don't know what to do next! 🤗@SanhEstPasMoihttps://t.co/yPkJR9f9Ua
Well worth a read…
— Mara Averick (@dataandme) September 22, 2020
"AI ethics is not an optimization problem" by @zkajdan https://t.co/jaNUOk8Ips pic.twitter.com/DB6Yv22mDh
New tutorial!🚀
— Adrian Rosebrock (@PyImageSearch) September 21, 2020
Intro to Automatic License/Number Plate Recognition with #OpenCV, #Python, and #DeepLearning 🚗🚚
- Detect license plates with OpenCV
- Extract characters
- #OCR license platehttps://t.co/SJyeME7sfV 👍#MachineLearning #ArtificialInteligence #AI #DataScience pic.twitter.com/UQk4Oq7m4V
