The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
https://www.ritchieng.com/the-incredible-pytorch/
https://github.com/ritchieng/the-incredible-pytorch
t.me/deeplearning_ai
.
https://www.ritchieng.com/the-incredible-pytorch/
https://github.com/ritchieng/the-incredible-pytorch
t.me/deeplearning_ai
.
GitHub
GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list of tutorials, papers, projects, communities andβ¦
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch. - GitHub - ritchieng/the-incredible-pytorch: The Incredible PyTorch: a curated list...
Want to jump ahead in artificial intelligence and/or digital pathology? Excited to share that after 2+ years of development PathML 2.0 is out! An open source #computational #pathology software library created by Dana-Farber Cancer Institute/Harvard Medical School and Weill Cornell Medicine led by Massimo Loda to lower the barrier to entry to #digitalpathology and #artificialintelligence , and streamline all #imageanalysis or #deeplearning workflows.
β Code: https://github.com/Dana-Farber-AIOS/pathml
β Code: https://github.com/Dana-Farber-AIOS/pathml
GitHub
GitHub - Dana-Farber-AIOS/pathml: Tools for computational pathology
Tools for computational pathology. Contribute to Dana-Farber-AIOS/pathml development by creating an account on GitHub.
9 Best Tools to Debug Python for 2022
https://www.ittsystems.com/best-tools-to-debug-python/
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.
https://www.ittsystems.com/best-tools-to-debug-python/
invite your friends πΉπΉ
@Deeplearning_ai
.
ITT Systems
9 Best Tools to Debug Python for 2025
Python is a high-level programming language, one of the top ten in the world in 2025. Find out the best tools to debug Python applications.
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PyAutoGUI is a cross-platform GUI automation Python module for human beings. Used to programmatically control the mouse & keyboard.
https://github.com/YashIndane/Call-of-Duty-
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https://github.com/YashIndane/Call-of-Duty-
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A lightweight vision library for performing large scale object detection & instance segmentation
Github: https://github.com/obss/sahi
Paper: https://arxiv.org/abs/2202.06934v1
Kaggle notebook: https://www.kaggle.com/remekkinas/sahi-slicing-aided-hyper-inference-yv5-and-yx
Dataset: https://paperswithcode.com/dataset/xview
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Github: https://github.com/obss/sahi
Paper: https://arxiv.org/abs/2202.06934v1
Kaggle notebook: https://www.kaggle.com/remekkinas/sahi-slicing-aided-hyper-inference-yv5-and-yx
Dataset: https://paperswithcode.com/dataset/xview
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Generative Occupancy Fields for 3D Surface-Aware Image Synthesis (NeurIPS 2021)
Project Page Paper Github
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Project Page Paper Github
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EG3D: Efficient Geometry-aware 3D Generative Adversarial Networks
https://youtu.be/cXxEwI7QbKg
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https://youtu.be/cXxEwI7QbKg
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YouTube
Efficient Geometry-aware 3D Generative Adversarial Networks | CVPR 2022
Project website: https://matthew-a-chan.github.io/eg3d
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing 3D GANs are eitherβ¦
Unsupervised generation of high-quality multi-view-consistent images and 3D shapes using only collections of single-view 2D photographs has been a long-standing challenge. Existing 3D GANs are eitherβ¦
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πΈUFO: segmentation @140+ FPSπΈ
πUnified Transformer Framework for Co-Segmentation, Co-Saliency & Salient Object Detection. All in one!
ππ’π π‘π₯π’π π‘ππ¬:
β Unified framework for co-segmentation
β Co-segmentation, co-saliency, saliency
β Block for long-range dependencies
β Able to reach for 140 FPS in inference
β The new SOTA on multiple datasets
β Source code under MIT License
[PAPER] [Source Code]
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πUnified Transformer Framework for Co-Segmentation, Co-Saliency & Salient Object Detection. All in one!
ππ’π π‘π₯π’π π‘ππ¬:
β Unified framework for co-segmentation
β Co-segmentation, co-saliency, saliency
β Block for long-range dependencies
β Able to reach for 140 FPS in inference
β The new SOTA on multiple datasets
β Source code under MIT License
[PAPER] [Source Code]
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@Deeplearning_ai
If you are learning Machine Learning and wants to make end-to-end Machine Learning real-world projects, then this website can be a great resource for you.
It has project bundle(Dragon bundle) comprising more than 550+ real-world projects in ML, DL, DS, CV and NLP and PYTHON3.
More details are showned in the image above.
- Each project comes with required Dataset, complete source code(Python3) and documentation along with explanatory comments so that even beginner can understand.
- Life time access and projects are getting updates each month.
You can download the list of complete 550+ projects from our website.
Visit our website for more information.
Website Link:
https://tensorprojects.com/dragonbundle
It has project bundle(Dragon bundle) comprising more than 550+ real-world projects in ML, DL, DS, CV and NLP and PYTHON3.
More details are showned in the image above.
- Each project comes with required Dataset, complete source code(Python3) and documentation along with explanatory comments so that even beginner can understand.
- Life time access and projects are getting updates each month.
You can download the list of complete 550+ projects from our website.
Visit our website for more information.
Website Link:
https://tensorprojects.com/dragonbundle
Forwarded from Artificial Intelligence && Deep Learning (Sh)
At DAIR.AI we heart open education. We are excited to share some of the best and most recent machine learning courses available on YouTube.
Hot topics:
1. Stanford CS229: Machine Learning
2. Practical Deep Learning for Coders (2020)
3. Deep Unsupervised Learning
4. Advanced NLP
5. Deep Learning for Computer Vision
6. Deep Reinforcement Learning
7. Full Stack Deep Learning
8. Self-Driving Cars (TΓΌbingen)
https://github.com/dair-ai/ML-YouTube-Courses
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Hot topics:
1. Stanford CS229: Machine Learning
2. Practical Deep Learning for Coders (2020)
3. Deep Unsupervised Learning
4. Advanced NLP
5. Deep Learning for Computer Vision
6. Deep Reinforcement Learning
7. Full Stack Deep Learning
8. Self-Driving Cars (TΓΌbingen)
https://github.com/dair-ai/ML-YouTube-Courses
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Free programming courses & quests with cash rewards for your time in one place ππ°
StackUp [app.stackup.dev] is a platform made for devs where you can learn about programming languages like Rust, Python, Go, Solidity, and other technologies, and earn while learning. Rewards are given after successful completion of quests.
With new campaigns every week, you can earn from a pool of over 10,000USD in cash rewards each month!
To sign up use code "machinelearning0" and gain early access: https://bit.ly/3FpfqHr
Hope it helps you to level up in the community and master different tools essential to your career as a developer! π
@deeplearning_ai
StackUp [app.stackup.dev] is a platform made for devs where you can learn about programming languages like Rust, Python, Go, Solidity, and other technologies, and earn while learning. Rewards are given after successful completion of quests.
With new campaigns every week, you can earn from a pool of over 10,000USD in cash rewards each month!
To sign up use code "machinelearning0" and gain early access: https://bit.ly/3FpfqHr
Hope it helps you to level up in the community and master different tools essential to your career as a developer! π
@deeplearning_ai
Lightweight Python library for adding real-time object tracking to any detector.
https://github.com/tryolabs/norfair
@deeplearning_ai
https://github.com/tryolabs/norfair
@deeplearning_ai
GitHub
GitHub - tryolabs/norfair: Lightweight Python library for adding real-time multi-object tracking to any detector.
Lightweight Python library for adding real-time multi-object tracking to any detector. - tryolabs/norfair
Forwarded from Artificial Intelligence && Deep Learning (SHOHRUH)
Accelerate AI training in a few lines of code without changing the training setup.
https://github.com/nebuly-ai/nebulgym
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https://github.com/nebuly-ai/nebulgym
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GitHub
GitHub - nebuly-ai/nos: Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through realβ¦
Module to Automatically maximize the utilization of GPU resources in a Kubernetes cluster through real-time dynamic partitioning and elastic quotas - Effortless optimization at its finest! - nebuly...
Free courses and quests in Coding & Web3.0 with cash rewards worth of 30 000USD π
https://bit.ly/3FpfqHr
Use code: "machinelearning0" when signing up to get access and start learning π
https://bit.ly/3FpfqHr
Use code: "machinelearning0" when signing up to get access and start learning π
PaMIR: Parametric Model-Conditioned Implicit Representation for Image-based Human Reconstruction.
Paper: https://arxiv.org/abs/2007.03858
Project Page: http://www.liuyebin.com/pamir/pamir.html
Source code: https://github.com/ZhengZerong/PaMIR
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Paper: https://arxiv.org/abs/2007.03858
Project Page: http://www.liuyebin.com/pamir/pamir.html
Source code: https://github.com/ZhengZerong/PaMIR
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@MachineLearning_Programming
Forwarded from Artificial Intelligence && Deep Learning (SHOHRUH)
CVPR 2022 Open Access...
Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
https://openaccess.thecvf.com/CVPR2022?day=2022-06-21
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Open Access versions, provided by the Computer Vision Foundation.
Except for the watermark, they are identical to the accepted versions; the final published version of the proceedings is available on IEEE Xplore.
https://openaccess.thecvf.com/CVPR2022?day=2022-06-21
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@Deeplearning_ai
Forwarded from Artificial Intelligence && Deep Learning (SHOHRUH)
Harvard CS109A #DataScience course materials β huge collection free & open!
1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
It will be really useful for you
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1. Lecture notes
2. R code, #Python notebooks
3. Lab material
4. Advanced sections
and more ...
https://harvard-iacs.github.io/2019-CS109A/pages/materials.html
It will be really useful for you
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@Deeplearning_ai