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ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning in python.

awesome-human-pose-estimation

A collection of awesome resources in Human Pose estimation.

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

braindecode

Deep learning software to decode EEG or MEG signals

code-of-learn-deep-learning-with-pytorch

This is code of book "Learn Deep Learning with PyTorch"

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

darts

Code for DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep-learning-with-tensorflow-book

深度学习开源书，基于TensorFlow 2.0实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

deepbleed

DeepBleed: 3D Volumetric Intracranial Hemorrhage Segmentation for Clinical Trials

deeplearning

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为15个章节，近20万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

deeprl

Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone

dsb2017

The solution of team 'grt123' in DSB2017

eeg-datasets

A list of all public EEG-datasets

learnpython

以撸代码的形式学习Python

lede

Lean's OpenWrt source

lihang-code

《统计学习方法》的代码实现

medical-data

medpy

Medical image processing in Python

ml_notes

机器学习算法的公式推导以及numpy实现

nnunet

openwrt-ci

OpenWrt CI 在线集成自动编译环境

predicting-hematoma-expansion-in-patients-that-had-a-stroke-using-ct-scan-images-and-deep-learning

Patients visit the hospital and have the first CT-scan image and after 24 hours they go for a follow-up CT-scan image. The main objective of these codes is using shallow learning methods and the corresponding clinical features to predict the expansion of hematoma after 24 hours. Convolutional Neural Network has been used!

predicting-hematoma-locations-in-stroke-patients

Predicting Hematoma Locations in Stroke Patients

prml

PRML algorithms implemented in Python

prml-1

Repository of notes, code and notebooks for the book Pattern Recognition and Machine Learning by Christopher Bishop