Leesoon1984's repositories
awesome-object-detection
Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
awesome-self-supervised-learning
A curated list of awesome Self-Supervised methods
AwesomeDeepLearning
My Deep Learning Notes
awsome-domain-adaptation
A collection of AWESOME things about domian adaptation
create-pascal-voc-dataset
Create PASCAL VOC 2007 dataset
deep_learning_object_detection
A paper list of object detection using deep learning.
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scutjy2015@163.com 版权所有,违权必究 Tan 2018.06
Detection
deeplearning detection
distiller
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller
ee227c.github.io
EE227C (Spring 2018) Course page
handson-ml
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Interview-Notebook
:calendar: 准备秋招学习笔记
interview_python
关于Python的面试题
leetCode-1
:pencil2: 算法相关知识储备 LeetCode with Python :books:
lihang_book_algorithm
致力于将李航博士《统计学习方法》一书中所有算法实现一遍
MachineLearning
Machine learning resources
metric-learn
Metric learning algorithms in Python
open-solution-salt-identification
Open solution to the TGS Salt Identification Challenge https://www.kaggle.com/c/tgs-salt-identification-challenge
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
steppy
Lightweight, Python library for fast and reproducible experimentation :microscope:
TensorFlow-Book
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
the-incredible-pytorch
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
WeakSupervisedSegmentationList
This repository contains lists of state-or-art weakly supervised semantic segmentation works