This tutorial from @andronovhopf on MLOps using GitHub Actions looks really promising. One of the cleanest APIs I have seen so far https://t.co/C4ugdwr15K
— Hamel Husain (@HamelHusain) July 26, 2020
This tutorial from @andronovhopf on MLOps using GitHub Actions looks really promising. One of the cleanest APIs I have seen so far https://t.co/C4ugdwr15K
— Hamel Husain (@HamelHusain) July 26, 2020
I published a guide to Keras preprocessing layers -- key new feature of the TensorFlow 2.3 release https://t.co/UjVTfIAKgW pic.twitter.com/CvQoHYf9rS
— François Chollet (@fchollet) July 25, 2020
Accelerating TF Lite 🏁⚡️
— TensorFlow (@TensorFlow) July 24, 2020
See how integration of the XNNPACK library with TensorFlow Lite improves neural network inference performance by 2.3X on average.
Learn more ↓ https://t.co/kWb9i5EgZd
A great blog post about some of the work my team is @nvidia is doing in the RecSys space building off of the amazing @rapidsai ecosystem. https://t.co/TxIkGqcZnl
— Even Oldridge (@Even_Oldridge) July 23, 2020
Quantization Aware Training 📝
— TensorFlow (@TensorFlow) July 23, 2020
In this TF Model Optimization Toolkit tutorial, you’ll learn the fundamentals of quantization aware training, how to use the TF Keras API, and internals of implementation.
Let’s get started → https://t.co/IX7eYA0Cto pic.twitter.com/dTNOsfdASX
This👇🏾 make it all worth it.@kaggle GM @ChrisDeotte used @RAPIDSai tsne, knn, & kmeans + @TensorFlow CNN in a complex pipeline (no bugs nor workarounds💪🏾) to find similar images compare train and test distributions and more https://t.co/ZQPqMCC9Nt https://t.co/Zeo5RQfSgR 🔥🔥🔥
— Joshua Patterson (@datametrician) July 18, 2020
Eager to use our newly released PruneBERT models to leverage extremely sparse (>= 95% ) networks?
— Hugging Face (@huggingface) July 17, 2020
Check out our new collaboration with the @octoml & TVM team!
Get an instant 3x inference speedup from Dense to Sparse models! 🔥🚀https://t.co/e2clSVj3Vb
A pair of new guides:
— Josh Gordon (@random_forests) July 17, 2020
Intro to graphs & functions: https://t.co/pMNyToa1Rq
Advanced autodiff: https://t.co/6pdPQweFnu
Faster than training from scratch - #Tutorial on how to fine-tune the English #GPT2 in any language with #Transformers, #Tokenizers & #fastai v2 (use case with Portuguese). Thanks to @huggingface, @jeremyphoward, @GuggerSylvain & @ailab_unb #NLP #DL #AI https://t.co/O21oSlW0OA
— Pierre Guillou (@pierre_guillou) July 15, 2020
New tutorial!🚀
— Adrian Rosebrock (@PyImageSearch) July 13, 2020
Implementing basic R-CNN object detector from scratch with #Keras and #TensorFlow 2:
- Train on your own datasets
- Detailed tutorial
- Includes #Python codehttps://t.co/vlxyGoQuO7 👍#DeepLearning #MachineLearning #ArtificialIntelligence #AI #DataScience pic.twitter.com/SFPER6aPqv
New tutorial on https://t.co/m6mT8SrKDD: speaker recognition from speech samples, using FFT & 1D CNN. By @fadibadine https://t.co/8pfJpUWwP2
— François Chollet (@fchollet) July 7, 2020
Amazing practical Reinforcement Learning tutorial by @FeryalMP in JAX https://t.co/Xz2CmAkwWg and Acme https://t.co/89WvKxYR3B - Feryal worked incredibly hard on this tutorial as a firm believer on teaching ML in every corner of the world. Very inspiring and empowering! https://t.co/zOGlZ2tBG4
— Nando de Freitas (@NandoDF) July 3, 2020