hyo009 Goto Github PK

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

adversarialnetspapers

The classical papers and codes about generative adversarial nets

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

apollo

An open autonomous driving platform

autoware

Open-source software for urban self-driving mobility

awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

book

Deep Learning 101 with PaddlePaddle

bootstrap

The most popular HTML, CSS, and JavaScript framework for developing responsive, mobile first projects on the web.

carnd-advanced-lane-lines-p4

carnd-alexnet-feature-extraction

This lab guides you through using AlexNet and TensorFlow to build a feature extraction network.

carnd-behavioral-cloning-p3

carnd-camera-calibration

Images and notebook for camera calibration

carnd-extended-kalman-filter-project

Self-Driving Car Nanodegree Program Starter Code for the Extended Kalman Filter Project

carnd-kidnapped-vehicle-project

carnd-lanelines-p1

carnd-mpc

carnd-traffic-sign-classifier-project-p2

carnd-transfer-learning-lab

carnd-vehicle-detection-p5

code

Code for the book "Mastering OpenCV with Practical Computer Vision Projects" by Packt Publishing 2012.

courserepo

cs224n

CS224n: Natural Language Processing with Deep Learning Assignments Winter, 2017

cs231n

cs294-112_hws

My solution to assignments in UC Berkeley CS294-112: Deep Reinforcement Learning

dbnet

DBNet: A Large-Scale Dataset for Driving Behavior Learning

deep-learning

Repo for the Deep Learning Nanodegree Foundations program.

deep-learning-for-medical-applications

Deep Learning Papers on Medical Image Analysis

deep-learning-in-python

deep-residual-networks

Deep Residual Learning for Image Recognition

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18个章节，50余万字。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