Linking pages
- GitHub - aymericdamien/TopDeepLearning: A list of popular github projects related to deep learning https://github.com/aymericdamien/TopDeepLearning 35 comments
- GitHub - igoradamenko/awesome-made-by-russians: The best open source projects that were made and mainly contributed by Russian developers https://github.com/igoradamenko/awesome-made-by-russians 10 comments
- GitHub - balavenkatesh3322/CV-pretrained-model: A collection of computer vision pre-trained models. https://github.com/balavenkatesh3322/CV-pretrained-model 5 comments
- How to win a Kaggle classification competition? | by OutisCJH | Analytics Vidhya | Medium https://medium.com/@outiscjh/how-to-win-a-kaggle-classification-competition-bcf87273968e 4 comments
- awesomo/PYTHON.md at master · lk-geimfari/awesomo · GitHub https://github.com/lk-geimfari/awesomeo/blob/master/languages/PYTHON.md 4 comments
- GitHub - rwightman/pytorch-image-models: PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more https://github.com/rwightman/pytorch-image-models 2 comments
- The birth of Albumentations. | by Vladimir Iglovikov | Medium | Medium https://medium.com/@iglovikov/the-birth-of-albumentations-fe38c1411cb3 0 comments
- Data Augmentation in Python: Everything You Need to Know - neptune.ai https://neptune.ai/blog/data-augmentation-in-python 0 comments
- GitHub - ml-tooling/best-of-ml-python: 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly. https://github.com/ml-tooling/best-of-ml-python 0 comments
- GitHub - selimsef/dfdc_deepfake_challenge: A prize winning solution for DFDC challenge https://github.com/selimsef/dfdc_deepfake_challenge 0 comments
- Image Augmentations with Albumentations | by Derrick Mwiti | Heartbeat https://heartbeat.fritz.ai/image-augmentations-with-albumentations-c1ca8fc78db7 0 comments
- Outperforming Google Cloud AutoML Vision with Tensorflow | by Shane Keller | Towards Data Science https://towardsdatascience.com/outperforming-google-cloud-automl-vision-with-tensorflow-and-google-deep-learning-vm-34a45e3860ae 0 comments
- GitHub - mbadry1/Top-Deep-Learning: Top 200 deep learning Github repositories sorted by the number of stars. https://github.com/mbadry1/Top-Deep-Learning 0 comments
- Image Segmentation: Tips and Tricks from 39 Kaggle Competitions | Neptune Blog https://neptune.ai/blog/image-segmentation-tips-and-tricks-from-kaggle-competitions 0 comments
- Multi-target in Albumentations. Many images, many masks, bounding boxes… | by Vladimir Iglovikov | PyTorch | Medium https://medium.com/@iglovikov/multi-target-in-albumentations-16a777e9006e 0 comments
- GitHub - academic/awesome-datascience: An awesome Data Science repository to learn and apply for real world problems. https://github.com/okulbilisim/awesome-datascience 0 comments
- Machine Learning Toolbox https://amitness.com/toolbox/ 0 comments
- GitHub - academic/awesome-datascience: An awesome Data Science repository to learn and apply for real world problems. https://github.com/bulutyazilim/awesome-datascience 0 comments
- Efficient PyTorch — Eliminating Bottlenecks | by Eugene Khvedchenya | Towards Data Science https://medium.com/@eugenekhvedchenya/efficient-pytorch-part-1-fe40ed5db76c 0 comments
- GitHub - lorepieri8/ai-techniques: AI Techniques for the Modern Problem Solver https://github.com/lorepieri8/ai-techniques 0 comments
Linked pages
- Apple https://apple.com 5523 comments
- Home | Microsoft Open Source https://opensource.microsoft.com/ 307 comments
- Stability AI https://stability.ai 69 comments
- Hugging Face – The AI community building the future. https://huggingface.co/ 57 comments
- The MIT License | Open Source Initiative https://opensource.org/licenses/MIT 15 comments
- Roboflow: Computer vision tools for developers and enterprises https://roboflow.com/ 3 comments
- H2O.ai | The fastest, most accurate AI Cloud Platform https://h2o.ai/ 1 comment
- Amazon Science homepage https://www.amazon.science/ 0 comments
- https://research.google 0 comments