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A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Python programs, usually short, of considerable difficulty, to perfect particular skills.
pytorch handbook是一本开源的书籍，目标是帮助那些希望和使用PyTorch进行深度学习开发和研究的朋友快速入门，其中包含的Pytorch教程全部通过测试保证可以成功运行
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
深度学习入门教程, 优秀文章, Deep Learning Tutorial
深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.
PRML algorithms implemented in Python
Best Practices, code samples, and documentation for Computer Vision.
Pytorch🍊🍉 is delicious, just eat it! 😋😋
links to conference publications in graph-based deep learning
Keras documentation, hosted live at keras.io
This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.
3D U-Net model for volumetric semantic segmentation written in pytorch
pytorch1.0 updated. Support cpu test and demo. (Use detectron2, it's a masterpiece)
Jupyter notebooks for learning how to use SimpleITK
[MICCAI 2019 Young Scientist Award] [MEDIA 2020 Best Paper Award] Models Genesis
A template for small scientific python projects
Released assignments for the Stanford's CS131 course on Computer Vision.
Stanford CS231n assignment in 2019 spring
Nested Hierarchical Transformer https://arxiv.org/pdf/2105.12723.pdf
Learn the Deep Learning for Computer Vision in three steps: theory from base to SotA, code in PyTorch, and space-repetition with Anki
This repository is a Python package with all of the functions and python libraries required for the Dartmouth fMRI Analysis Course taught by Prof Luke Chang, PhD.