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09/10/2019
Pythia: open-source framework for multimodal AI models - Facebook Engineering 09/10/2019

Pythia : New deep learning framework from Facebook

Pythia is a deep learning framework that supports multitasking in the vision and language domain. Built on our open-source framework, the modular, plug-and-play design enables researchers to quickly build, reproduce, and benchmark AI models. is designed for vision and language tasks, such as answering questions related to visual data and automatically generating image caption

Link: https://engineering.fb.com/ai-research/pythia/
GitHub: https://github.com/facebookresearch/pythia
more : https://arxiv.org/abs/1807.09956

Pythia: open-source framework for multimodal AI models - Facebook Engineering Pythia is a new open source deep learning framework that enables researchers to quickly build, reproduce, and benchmark AI models.

huggingface/transformers 09/10/2019

Awesome news for all NLP people 🔥! PyTorch-Transformers 1.0 is out (formerly known as pytorch-pretrained-bert). It now includes 6 SOTA NLP models: Bert, GPT, GPT-2, Transformer-XL, XLNet, XLM and also 27 pre-trained weights. There's also a new unified API for models and tokenizer. Check the release note for more information and also the project in general. Great work by the team at Hugging Face. Can't wait to use it for our own projects.

🔤 Code: https://github.com/huggingface/transformers
📘 Documentation: https://huggingface.co/transformers/
📝 Release note: https://github.com/huggingface/transformers/releases/tag/v1.0.0

huggingface/transformers 🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch. - huggingface/transformers

tensorflow/tensorflow 09/10/2019

TensorFlow 2.0.0

Release 2.0.0 - Major Features and Improvements

https://github.com/tensorflow/tensorflow/releases

https://medium.com/tensorflow/tensorflow-2-0-is-now-available-57d706c2a9ab

TensorFlow 2.0 focuses on simplicity and ease of use, featuring updates like:

- Easy model building with Keras and eager ex*****on.
- Robust model deployment in production on any platform.
- Powerful experimentation for research.
- API simplification by reducing duplication and removing deprecated endpoints.

For details on best practices with 2.0, see the Effective 2.0 guide - https://www.tensorflow.org/guide/effective_tf2

tensorflow/tensorflow An Open Source Machine Learning Framework for Everyone - tensorflow/tensorflow

Start Here with Computer Vision, Deep Learning, and OpenCV - PyImageSearch 09/10/2019

A step-by-step guide on how to learn Computer Vision, Deep Learning, and OpenCV by pyimagesearch - Adrian Rosebrock

https://www.pyimagesearch.com/start-here/

Inside the guide you'll find step-by-step, easy to follow instructions on:

Getting started with OpenCV
Deep Learning (Keras and TensorFlow)
Face applications (including face detection, facial landmarks, and face recognition)
Optical Character Recognition (OCR)
Object detection (SSDs, YOLO, etc.)
Object tracking
Instance segmentation (Mask R-CNNs)
CV and DL on embedded/IoT devices (RPi, Movidius NCS Google Coral, Jetson Nano)
Medical Computer Vision
..and much more!

Start Here with Computer Vision, Deep Learning, and OpenCV - PyImageSearch

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