Today, I am launching the my PyTorch course is, a highly specialized autograd course for intermediate to advanced PyTorch users.
Because I know some PyTorch but am clueless about marketing, it is hidden behind registration and I don't post the link.
https://lernapparat.de/launching-autograd-course/
Because I know some PyTorch but am clueless about marketing, it is hidden behind registration and I don't post the link.
https://lernapparat.de/launching-autograd-course/
YOLOX: Exceeding YOLO Series in 2021
Anchor-free version of YOLO series
Won the 1st Place on Streaming
Perception Challenge (Workshop on Autonomous Driving
at CVPR 2021)
https://github.com/Megvii-BaseDetection/YOLOX
Anchor-free version of YOLO series
Won the 1st Place on Streaming
Perception Challenge (Workshop on Autonomous Driving
at CVPR 2021)
https://github.com/Megvii-BaseDetection/YOLOX
FREE comprehensive 569-page eBook on Applications of Deep Neural Networks by Jeff Heaton
https://www.datasciencecentral.com/profiles/blogs/free-500-page-book-on-applications-of-deep-neural-networks-1
https://www.datasciencecentral.com/profiles/blogs/free-500-page-book-on-applications-of-deep-neural-networks-1
Course on Geometric Deep Learning
Bronstein et al.: https://geometricdeeplearning.com/lectures/
Bronstein et al.: https://geometricdeeplearning.com/lectures/
Artificial Intelligence Birth story
https://twitter.com/Aiindiaai/status/1424906514435739650?s=09
https://twitter.com/Aiindiaai/status/1424906514435739650?s=09
Twitter
Artificial Intelligence 🤖💡✍️
How Artificial intelligence💡 was born? While #artificialintelligence (#AI) is among today’s most popular topics, a commonly forgotten fact is that it was actually born in late 1950s. The story of #AI birth is interesting.
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Oriented R-CNN for Object Detection
Github: https://github.com/jbwang1997/OBBDetection
BboxToolkit: https://github.com/jbwang1997/BboxToolkit
Paper: https://arxiv.org/abs/2104.1122
Github: https://github.com/jbwang1997/OBBDetection
BboxToolkit: https://github.com/jbwang1997/BboxToolkit
Paper: https://arxiv.org/abs/2104.1122
GitHub
GitHub - jbwang1997/OBBDetection: OBBDetection is an oriented object detection library, which is based on MMdetection.
OBBDetection is an oriented object detection library, which is based on MMdetection. - jbwang1997/OBBDetection
A blogpost from Apple summarizing their research on generative model for scene level radiance fields (GSN), ICCV 2021
https://machinelearning.apple.com/research/learning-to-generate-radiance-fields
https://machinelearning.apple.com/research/learning-to-generate-radiance-fields
Apple Machine Learning Research
Learning to Generate Radiance Fields of Indoor Scenes
People have an innate capability to understand the 3D visual world and make predictions about how the world could look from different points…
👨🎓 Best Resources to Learn Natural Language Processing in 2021
https://www.kdnuggets.com/2021/09/best-resources-learn-natural-language-processing-2021.html
https://www.kdnuggets.com/2021/09/best-resources-learn-natural-language-processing-2021.html
KDnuggets
Best Resources to Learn Natural Language Processing in 2021
In this article, the author has listed listed all the best resources to learn natural language processing including Online Courses, Tutorials, Books, and YouTube Videos.
Anybody heard about semantic segmentation. Yeah, me too!
This article goes step by step into how semantic segmentation provides context to images through pixel-accuracy.
A very informative read that answers all the questions on the topic.
https://blog.superannotate.com/guide-to-semantic-segmentation/
This article goes step by step into how semantic segmentation provides context to images through pixel-accuracy.
A very informative read that answers all the questions on the topic.
https://blog.superannotate.com/guide-to-semantic-segmentation/
SuperAnnotate
Semantic segmentation: Complete guide [Updated 2024] | SuperAnnotate
Check out our guide on semantic segmentation and its use cases to learn more about how to properly label specific regions of an image.
Dual deployments on Vertex AI🔥🔥
Google introduced new deployment techniques for mobile and web.
https://cloud.google.com/blog/topics/developers-practitioners/dual-deployments-vertex-ai
Google introduced new deployment techniques for mobile and web.
https://cloud.google.com/blog/topics/developers-practitioners/dual-deployments-vertex-ai
Google Cloud Blog
Dual deployments on Vertex AI | Google Cloud Blog
DeepMind in collaboration with University College London released the "Reinforcement Learning Lecture Series 2021"
Website: https://deepmind.com/learning-resources/reinforcement-learning-series-2021
Lecture Video: https://youtube.com/playlist?list=PLqYmG7hTraZDVH599EItlEWsUOsJbAodm
Website: https://deepmind.com/learning-resources/reinforcement-learning-series-2021
Lecture Video: https://youtube.com/playlist?list=PLqYmG7hTraZDVH599EItlEWsUOsJbAodm
Google DeepMind
Artificial intelligence could be one of humanity’s most useful inventions. We research and build safe artificial intelligence systems. We're committed to solving intelligence, to advance science...
Hello sir/ma'am,
I am Yashita Bawane, VII semester student of B. Arch from National Institute of Technology Raipur. I am working on my research paper titled "Enhancing productivity through daylighting in corporate workspaces".
As a part of my research work, I am undertaking a survey to know the lighting preferences of the corporate employees and how it relates to the quality of output.
I would be grateful if you spare some time and fill in the questionnaires. This survey would take 2-3 minutes to complete. Be assured that all the details will be kept confidential and will be used for academic purpose only.
Thank you in advance
https://forms.gle/5k46CdaFnG3HAJzw8
I am Yashita Bawane, VII semester student of B. Arch from National Institute of Technology Raipur. I am working on my research paper titled "Enhancing productivity through daylighting in corporate workspaces".
As a part of my research work, I am undertaking a survey to know the lighting preferences of the corporate employees and how it relates to the quality of output.
I would be grateful if you spare some time and fill in the questionnaires. This survey would take 2-3 minutes to complete. Be assured that all the details will be kept confidential and will be used for academic purpose only.
Thank you in advance
https://forms.gle/5k46CdaFnG3HAJzw8
Google Docs
Survey
Greetings sir/ma'am!
The form intends to gather information about corporate work preferences for my analytical architectural thesis titled "Enhancing productivity through daylight in corporate work spaces" .
The form intends to gather information about corporate work preferences for my analytical architectural thesis titled "Enhancing productivity through daylight in corporate work spaces" .
PySlowFast library by Facebook AI just added the neural Transformers support ☑☑
👉PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficient training
Highlights:
✅SlowFast Networks for Video Recognition
✅Supporting Non-local Neural Networks
✅Multigrid Method for Efficiently Training Video Models
✅X3D: Progressive Expansion for Efficient Video Rec.
✅Multiscale Vision Transformers (new!)
🚩Link to source code
👉PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficient training
Highlights:
✅SlowFast Networks for Video Recognition
✅Supporting Non-local Neural Networks
✅Multigrid Method for Efficiently Training Video Models
✅X3D: Progressive Expansion for Efficient Video Rec.
✅Multiscale Vision Transformers (new!)
🚩Link to source code
GitHub
GitHub - facebookresearch/SlowFast: PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models. - facebookresearch/SlowFast
Deploy your PyTorch model to Production
This tutorial aims to teach you how to deploy your recently trained model in PyTorch as an API using Python.
https://www.kdnuggets.com/2019/03/deploy-pytorch-model-production.html
This tutorial aims to teach you how to deploy your recently trained model in PyTorch as an API using Python.
https://www.kdnuggets.com/2019/03/deploy-pytorch-model-production.html
KDnuggets
Deploy your PyTorch model to Production
This tutorial aims to teach you how to deploy your recently trained model in PyTorch as an API using Python.
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VIEW IN TELEGRAM
Believe it or not, this is not originally a video. It was made from a collection of photos. Sounds interesting?
Learn more about video from this paper 👇
AI Synthesizes Smooth Videos from a Couple of Images!
Paper link: https://arxiv.org/pdf/2110.06635.pdf.
Code: https://github.com/darglein/ADOP
Learn more about video from this paper 👇
AI Synthesizes Smooth Videos from a Couple of Images!
Paper link: https://arxiv.org/pdf/2110.06635.pdf.
Code: https://github.com/darglein/ADOP
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