Stars
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Repository of algorithms implemented in pure assembly
Master programming by recreating your favorite technologies from scratch.
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Bootstrap yourself to write an OS from scratch. A book for self-learner.
Code for "DeepDRR: A Catalyst for Machine Learning in Fluoroscopy-guided Procedures". https://arxiv.org/abs/1803.08606
🦜🔗 Build context-aware reasoning applications
Resources of the paper “Deep Learning to Segment Pelvic Bones: Large-scale CT Datasets and Baseline Models”.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
[eBioMedicine] Deep-learning-assisted detection and segmentation of rib fractures from CT scans: Development and validation of FracNet
LATEX: TikZ package for drawing neural networks. Also available on CTAN at https://www.ctan.org/tex-archive/graphics/pgf/contrib/neuralnetwork
A faster implementation of PointNet++ based on PyTorch.
OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)
Implementation of the Point Transformer layer, in Pytorch
This is an unofficial implementation of the Point Transformer paper.
Exploring Self-attention for Image Recognition, CVPR2020.
DataLoader subclass for PyTorch to work with HDF5 files.
A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Personal implementation of PointNet in TF 2.0