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DeepLearning-500-questions - Readme

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Archivy is a self-hosted knowledge repository that allows you to safely preserve useful content that contributes to your knowledge bank.
mall-swarm
mall-swarm是一套微服务商城系统,采用了 Spring Cloud Hoxton & Alibaba、Spring Boot 2.3、Oauth2、MyBatis、Docker、Elasticsearch等核心技术,同时提供了基于Vue的管理后台方便快速搭建系统。mall-swarm在电商业务的基础集成了注册中心、配置中心、监控中心、网关等系统功能。文档齐全,附带全套Spring Clou
umami
Umami is a simple, fast, website analytics alternative to Google Analytics.
nl-covid19-notification-app-android
Android sources for the Dutch Covid19 Notification App
contenidos
Material del curso IIC2233 Programación Avanzada ?
locast2plex
A very simple script to connect locast to Plex's live tv/dvr feature.
h1st
H1st AI solves the critical “cold-start” problem of Industrial AI: encoding human expertise to augment the lack of data, while building a smooth transition toward a machine-learning future. This probl
minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Catch2
A modern, C++-native, header-only, test framework for unit-tests, TDD and BDD - using C++11, C++14, C++17 and later (or C++03 on the Catch1.x branch)
libra
Ergonomic machine learning.
annie
? Fast, simple and clean video downloader
spotMicro
Spot Micro Quadripeg Project
LeetCode-Go
✅ Solutions to LeetCode by Go, 100% test coverage, runtime beats 100% / LeetCode 题解
bootcamp-gostack-desafios
Repositório contendo todos os desafios dos módulos do Bootcamp Gostack
NoVmp
A static devirtualizer for VMProtect x64 3.x. powered by VTIL.
fullcalendar
Full-sized drag & drop event calendar
latexify_py
Generates LaTeX math description from Python functions.
vue-nodejs-youtube-clone
This is the frontend (VueJS) of the Youtube clone called VueTube.
youtube-clone-nodejs-api
VueTube is a YouTube clone built with nodejs, expressjs & mongodb. This is the RESTful API repository.
Behinder
“冰蝎”动态二进制加密网站管理客户端
low-level-design-primer

E-commerce-Complete-Flutter-UI

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.
aws-machine-learning-university-accelerated-tab

aws-machine-learning-university-accelerated-cv

mogollar
A MongoDB UI built with Electron
BespokeSynth
Software modular synth
desafio-1-2020

desafio-1-2020

kosmonaut
A web browser engine for the space age ?
aws-machine-learning-university-accelerated-nlp

fastbook
Draft of the fastai book
Hierarchical-Localization
Visual localization made easy
TypeScript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
Penetration_Testing_POC
渗透测试有关的POC、EXP、脚本、提权、小工具等,欢迎补充、完善---About penetration-testing python-script poc getshell csrf xss cms php-getshell domainmod-xss penetration-testing-poc csrf-webshell cobub-razor cve rce sql sql-poc p
God-Of-BigData
大数据面试题,大数据成神之路开启...Flink/Spark/Hadoop/Hbase/Hive...
OSCPRepo
A list of commands, scripts, resources, and more that I have gathered and attempted to consolidate for use as OSCP (and more) study material. Commands in 'Usefulcommands' Keepnote. Bookmarks and readi
drogon
Drogon: A C++14/17 based HTTP web application framework running on Linux/macOS/Unix/Windows
papercups
Open-source live customer chat
jupyter-book
Build interactive, publication-quality documents from Jupyter Notebooks
awesome-java
Collection of awesome Java project on Github(Github 上非常棒的 Java 开源项目集合).
espflix
A free video streaming service that runs on a ESP32
servo
The Servo Browser Engine
halfmoon
Front-end framework with a built-in dark mode, designed for rapidly building beautiful dashboards and product pages.
eventnative
EventNative is an open-source data collection framework
go-github
Go library for accessing the GitHub API
yam-protocol
A stablizing reserve currency protocol
mmdetection3d
OpenMMLab's next-generation platform for general 3D object detection.
sherlock
? Hunt down social media accounts by username across social networks
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
clean-code-javascript
? Clean Code concepts adapted for JavaScript
laravel-admin
Build a full-featured administrative interface in ten minutes
OpenJailbreak
GeoSn0w's OpenJailbreak Project, an open-source iOS 11 to iOS 13 Jailbreak project & vault.
azure-quickstart-templates
Azure Quickstart Templates
nodejs.dev
A new Node.js resource built using Gatsby.js with React.js, TypeScript, Emotion, and Remark.
KOOM
KOOM is an OOM killer on mobile platform by Kwai.
bevy
A refreshingly simple data-driven game engine built in Rust
eat_pytorch_in_20_days
Pytorch?? is delicious, just eat it! ??
datasets
? 2,000,000+ Unsplash images made available for research and machine learning
malwoverview
Malwoverview is a first response tool to perform an initial and quick triage in a directory containing malware samples, specific malware sample, suspect URL and domains. Additionally, it allows to dow
streisand
Streisand sets up a new server running your choice of WireGuard, OpenConnect, OpenSSH, OpenVPN, Shadowsocks, sslh, Stunnel, or a Tor bridge. It also generates custom instructions for all of these serv
LeetCode
LeetCode刷题记录
IntelOwl
Intel Owl: analyze files, domains, IPs in multiple ways from a single API at scale
archive-program
The GitHub Archive Program & Arctic Code Vault
rancher
Complete container management platform
Noctilucent
Using TLS 1.3 to evade censors, bypass network defenses, and blend in with the noise
data-science
? Path to a free self-taught education in Data Science!
FigmaToCode
Generate responsive pages and apps on Tailwind, Flutter and SwiftUI.
twitter-clone

my-arsenal-of-aws-security-tools
List of open source tools for AWS security: defensive, offensive, auditing, DFIR, etc.
InvoiceNet
Deep neural network to extract intelligent information from invoice documents.
macOS_Big_Sur_icons_replacements
Replacement icons for popular apps in the style of macOS Big Sur
AnimeGANv2
[Open Source]. The improved version of AnimeGAN.
bluezone-app
Bluezone - Bảo vệ mình, bảo vệ cộng đồng
awesome-sysadmin
A curated list of amazingly awesome open source sysadmin resources inspired by Awesome PHP.
facebook-scripts-dom-manipulation
An open-source project includes many scripts with no Access Token needed for Facebook users by directly manipulating the DOM.
MCinaBox
MCinaBox - A Minecraft Java Edition Launcher on Android
ai-economist
Foundation is a flexible, modular, and composable framework to model socio-economic behaviors and dynamics with both agents and governments. This framework can be used in conjunction with reinforcemen
TikTok-Shares-Botter
Adds TikTok Shares for you.
prefect
The easiest way to automate your data
tuya-convert
A collection of scripts to flash Tuya IoT devices to alternative firmwares
crush
Crush is an attempt to make a command line shell that is also a powerful modern programming language.
pyre-check
Performant type-checking for python.
polkadot
Polkadot Node Implementation
incyber

mesh
Cloud native service mesh for the rest of us.
V2rayU
V2rayU,基于v2ray核心的mac版客户端,用于科学上网,使用swift编写,支持vmess,shadowsocks,socks5等服务协议,支持订阅, 支持二维码,剪贴板导入,手动配置,二维码分享等
TLS-poison

heroicons
A set of free MIT-licensed high-quality SVG icons for UI development.
react-native
A framework for building native apps with React.
gui.cs
Console-based user interface toolkit for .NET applications.
Atlas
Atlas: End-to-End 3D Scene Reconstruction from Posed Images
aws-sdk-go
AWS SDK for the Go programming language.
charts
Curated applications for Kubernetes
pybind11
Seamless operability between C++11 and Python
mediapipe
MediaPipe is the simplest way for researchers and developers to build world-class ML solutions and applications for mobile, edge, cloud and the web.
proffy-discovery
A proposta do projeto é uma aplicação que possa ligar quem deseja aprender, com quer ensinar. É possível encontrar alunos para o que você leciona, ou encontrar o professor para aquela matéria que você
mixer
Add-on for real-time collaboration in Blender.
iOS-DeviceSupport
This repository holds the device support files for the iOS, and I will update it regularly.
simdjson
Parsing gigabytes of JSON per second
amplify-js
A declarative JavaScript library for application development using cloud services.
lottie-ios
An iOS library to natively render After Effects vector animations
Faze4-Robotic-arm
All files for 6 axis robot arm with cycloidal gearboxes .
xiaobaiyang

Javascript
A repository for All algorithms implemented in Javascript (for educational purposes only)
blog-post-workflow
Show your latest blog posts from any sources or StackOverflow activity on your GitHub profile/project readme automatically using the RSS feed
reverse-interview
Questions to ask the company during your interview
expo
An open-source platform for making universal native apps with React. Expo runs on Android, iOS, and the web.
955.WLB
955 不加班的公司名单 - 工作 955,work–life balance (工作与生活的平衡)
A-to-Z-Resources-for-Students
✅ Curated list of resources for college students
TDengine
An open-source big data platform designed and optimized for the Internet of Things (IoT).
django-jazzmin
Jazzy theme for Django
full-stack-fastapi-postgresql
Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.
Reflection_Summary
算法理论基础知识应知应会
Best-websites-a-programmer-should-visit
? Some useful websites for programmers.
bpytop
Linux/OSX/FreeBSD resource monitor
TelemetrySourcerer
Enumerate and disable common sources of telemetry used by AV/EDR.
instagrabber
InstaGrabber, the open-source Instagram client for Android. Originally by @AwaisKing.
pe_tree

Powershell-Scripts
Helpful list of powershell scripts I have found/created
drawio
Source to app.diagrams.net
analytics
Simple and privacy-friendly alternative to Google Analytics
pycaret
An open source, low-code machine learning library in Python
Ciphey
Automated decryption tool
Data-Science-Interview-Resources
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
ps4-ipv6-uaf

UNSAM_2020c2_Python
Curso de programación en Python - 2do cuatrimestre 2020 - UNSAM
gpu.js
GPU Accelerated JavaScript
how-to-secure-anything
How to systematically secure anything: a repository about security engineering
paperview
A high performance X11 animated wallpaper setter
core
? JAVClub - 让你的大姐姐不再走丢
home-cloud
The "cloud" at home
haoel.github.io

InstaPy
? Instagram Bot - Tool for automated Instagram interactions
bat
A cat(1) clone with wings.
DeOldify
A Deep Learning based project for colorizing and restoring old images (and video!)
educative.io_courses
this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack
rustlings
? Small exercises to get you used to reading and writing Rust code!
trackerslist
Updated list of public BitTorrent trackers
Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
mobile
React Native client application for COVID Shield on iOS and Android
binary_search
A collection of improved binary search algorithms.
mirai

TapTap
Port of the double tap on back of device feature from Android 11 to any armv8 Android device
complete-javascript-course
Starter files, final projects and FAQ for my Complete JavaScript course
icons
Official open source SVG icon library for Bootstrap.
oneflow
OneFlow is a performance-centered and open-source deep learning framework.
ml-engineer-roadmap
WIP: Roadmap to becoming a machine learning engineer in 2020
hvmi
Hypervisor Memory Introspection Core Library
fhe-toolkit-linux
IBM Fully Homomorphic Encryption Toolkit For Linux
teenyicons
Tiny minimal 1px icons designed to fit in the smallest places.
project-citadel
An open source project management tool with Kanban boards
covid-alert-app
Exposure notification client application / Application client de notification d'exposition
ChromeAppHeroes
?谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
SSPanel-Uim
SSPanel V3 魔改再次修改版
UnusualVolumeDetector
Gets the last 5 months of volume history for every ticker, and alerts you when a stock's volume exceeds 10 standard deviations from the mean within the last 3 days
formik
Build forms in React, without the tears ?
learn-cantrill-io-labs
Standard and Advanced Demos for learn.cantrill.io courses
TransCoder
Public release of the TransCoder research project https://arxiv.org/pdf/2006.03511.pdf
bounty-targets-data
This repo contains hourly-updated data dumps of bug bounty platform scopes (like Hackerone/Bugcrowd/Intigriti/etc) that are eligible for reports
CtCI-6th-Edition
Cracking the Coding Interview 6th Ed. Solutions
windows95
?? Windows 95 in Electron. Runs on macOS, Linux, and Windows.
SkyArk
SkyArk helps to discover, assess and secure the most privileged entities in Azure and AWS
interviews
Everything you need to know to get the job.
Android-Analysis
Getting Genymotion & Burpsuite setup for Android Mobile App Analysis
detext
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
awesome-java
A curated list of awesome frameworks, libraries and software for the Java programming language.
workflow

tye
Tye is a tool that makes developing, testing, and deploying microservices and distributed applications easier. Project Tye includes a local orchestrator to make developing microservices easier and the
java-design-patterns
Design patterns implemented in Java
java8-tutorial
Modern Java - A Guide to Java 8
generator-jhipster
JHipster is a development platform to quickly generate, develop, & deploy modern web applications & microservice architectures.
stayaway-app
Official repository for the STAYAWAY COVID mobile application
api-guidelines
Microsoft REST API Guidelines
win10script
This is the Ultimate Windows 10 Script from a creation from multiple debloat scripts and gists from github.
tutorials
Just Announced - "Learn Spring Security OAuth":
Otto
Otto makes machine learning an intuitive, natural language experience.? Facebook AI Challenge winner
first-order-model
This repository contains the source code for the paper First Order Motion Model for Image Animation
laravel-best-practices
Laravel best practices
hiring-without-whiteboards
⭐️ Companies that don't have a broken hiring process
PyTorch_YOLOv4
PyTorch implementation of YOLOv4
macintosh.js
A virtual Apple Macintosh with System 8, running in Electron. I'm sorry.
QuickCut
Your most handy video processing software
Super-mario-bros-PPO-pytorch
Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
arrow
Apache Arrow is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficien
swift
The Swift Programming Language
flutter
Flutter makes it easy and fast to build beautiful apps for mobile and beyond.
pikvm
Open and cheap DIY IP-KVM based on Raspberry Pi
ILSpy
.NET Decompiler with support for PDB generation, ReadyToRun, Metadata (&more) - cross-platform!
aluraflix
⚛️ Projeto feito durante a Imersão React da Alura
starship
☄?️ The minimal, blazing-fast, and infinitely customizable prompt for any shell!
leonsans
Leon Sans is a geometric sans-serif typeface made with code in 2019 by Jongmin Kim.
MCVmComputers
Order computer parts from a satellite orbiting around your minecraft world and build actual working computers with them!

DeepLearning-500-questions

LINK
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scutjy2015@163.com 版权所有,违权必究 Tan 2018.06

禁止转载,禁止转载,禁止转载!

GitHub上非最新内容,最新内容请期待新书。

学习交流群


学习交流群

理解CNN、CNN可视化 CNN-Visualization

https://github.com/scutan90/CNN-Visualization

深度学习乳腺癌识别与诊断

https://github.com/scutan90/Breast-imaging-Deeplearning

英文版本

English version

1. 版权声明

请尊重作者的知识产权,版权所有,翻版必究。 未经许可,严禁转发内容!
请大家一起维护自己的劳动成果,进行监督。 未经许可, 严禁转发内容!     2018.6.27 TanJiyong

2. 概述

本项目是大家对AI的相关知识进行整合,集思广益,以便形成 内容充实,覆盖全面的文集。

3. 加入以及文档规范

1、寻求有愿意继续完善的朋友、编辑、写手;如有意合作,完善出书(成为共同作者)。
2、所有提交内容的贡献者,将会在文中体现贡献者个人信息(例:大佬-西湖大学)
3、为了让内容更充实完善,集思广益,欢迎Fork该项目并参与编写。请在修改MD文件的同时(或直接留言)备注自己的姓名-单位(大佬-斯坦福大学),一经采纳,会在原文中显示贡献者的信息,谢谢!
4、推荐使用typora-Markdown阅读器:https://typora.io/

设置: 文件->偏好设置

都打勾

都打勾

例子:

### 3.3.2 如何寻找超参数的最优值?(贡献者:大佬-斯坦福大学)

在使用机器学习算法时,总有一些难搞的超参数。例如权重衰减大小,高斯核宽度等等。算法不会设置这些参数,而是需要你去设置它们的值。设置的值对结果产生较大影响。常见设置超参数的做法有:

1. 猜测和检查:根据经验或直觉,选择参数,一直迭代。
2. 网格搜索:让计算机尝试在一定范围内均匀分布的一组值。
3. 随机搜索:让计算机随机挑选一组值。
4. 贝叶斯优化:使用贝叶斯优化超参数,会遇到贝叶斯优化算法本身就需要很多的参数的困难。
5. 在良好初始猜测的前提下进行局部优化:这就是 MITIE 的方法,它使用 BOBYQA 算法,并有一个精心选择的起始点。由于 BOBYQA 只寻找最近的局部最优解,所以这个方法是否成功很大程度上取决于是否有一个好的起点。在 MITIE 的情下,我们知道一个好的起点,但这不是一个普遍的解决方案,因为通常你不会知道好的起点在哪里。从好的方面来说,这种方法非常适合寻找局部最优解。稍后我会再讨论这一点。
6. 最新提出的 LIPO 的全局优化方法。这个方法没有参数,而且经验证比随机搜索方法好。

4. 贡献与项目概览

已提交MD版本章节:请查看MarkDown

5. 更多

  1. 寻求有愿意继续完善的朋友、编辑、写手; 如有意合作,完善出书(成为共同作者)。
    所有提交内容的贡献者,将会在文中体现贡献者个人信息(大佬-西湖大学)。

  2. 联系方式:请联系scutjy2015@163.com (唯一官方邮箱); 微信Tan:

    (进群先在MD版本增加、改善、提交内容后,更易进群,享受分享知识帮助他人。)

  3. Markdown阅读器推荐:https://typora.io/ 免费且对于数学公式显示支持的比较好。

  4. 注意,现出现不法分子冒充发起人,请广大伙伴儿知悉!

  5. 接下来,将提供MD版本,大家一起编辑完善,敬请期待!希望踊跃提建议,补充修改内容!

6. 友情链接

FlyAI-AI竞赛平台

7. 目录

第一章 数学基础 1

1.1 标量、向量、张量之间的联系 1
1.2 张量与矩阵的区别? 1
1.3 矩阵和向量相乘结果 1
1.4 向量和矩阵的范数归纳 1
1.5 如何判断一个矩阵为正定? 2
1.6 导数偏导计算 3
1.7 导数和偏导数有什么区别? 3
1.8 特征值分解与特征向量 3
1.9 奇异值与特征值有什么关系? 4
1.10 机器学习为什么要使用概率? 4
1.11 变量与随机变量有什么区别? 4
1.12 常见概率分布? 5
1.13 举例理解条件概率 9
1.14 联合概率与边缘概率联系区别? 10
1.15 条件概率的链式法则 10
1.16 独立性和条件独立性 11
1.17 期望、方差、协方差、相关系数总结 11

第二章 机器学习基础 14

2.1 各种常见算法图示 14 2.2 监督学习、非监督学习、半监督学习、弱监督学习? 15
2.3 监督学习有哪些步骤 16
2.4 多实例学习? 17
2.5 分类网络和回归的区别? 17
2.6 什么是神经网络? 17
2.7 常用分类算法的优缺点? 18
2.8 正确率能很好的评估分类算法吗? 20
2.9 分类算法的评估方法? 20
2.10 什么样的分类器是最好的? 22
2.11 大数据与深度学习的关系 22
2.12 理解局部最优与全局最优 23
2.13 理解逻辑回归 24
2.14 逻辑回归与朴素贝叶斯有什么区别? 24
2.15 为什么需要代价函数? 25
2.16 代价函数作用原理  25
2.17 为什么代价函数要非负? 26
2.18 常见代价函数? 26
2.19 为什么用交叉熵代替二次代价函数 28
2.20 什么是损失函数? 28
2.21 常见的损失函数 28
2.22 逻辑回归为什么使用对数损失函数? 30
0.00 对数损失函数是如何度量损失的? 31
2.23 机器学习中为什么需要梯度下降? 32
2.24 梯度下降法缺点? 32
2.25 梯度下降法直观理解? 32
2.23 梯度下降法算法描述? 33
2.24 如何对梯度下降法进行调优? 35
2.25 随机梯度和批量梯度区别? 35
2.26 各种梯度下降法性能比较 37
2.27 计算图的导数计算图解? 37
2.28 线性判别分析(LDA)思想总结 39
2.29 图解LDA核心思想 39
2.30 二类LDA算法原理? 40
2.30 LDA算法流程总结? 41
2.31 LDA和PCA区别? 41
2.32 LDA优缺点? 41
2.33 主成分分析(PCA)思想总结 42
2.34 图解PCA核心思想 42
2.35 PCA算法推理 43
2.36 PCA算法流程总结 44
2.37 PCA算法主要优缺点 45
2.38 降维的必要性及目的 45
2.39 KPCA与PCA的区别? 46
2.40 模型评估 47
2.40.1模型评估常用方法? 47
2.40.2 经验误差与泛化误差 47
2.40.3 图解欠拟合、过拟合 48
2.40.4 如何解决过拟合与欠拟合? 49
2.40.5 交叉验证的主要作用? 50
2.40.6 k折交叉验证? 50
2.40.7 混淆矩阵 50
2.40.8 错误率及精度 51
2.40.9 查准率与查全率 51
2.40.10 ROC与AUC 52
2.40.11 如何画ROC曲线? 53
2.40.12 如何计算TPR,FPR? 54
2.40.13 如何计算Auc? 56
2.40.14 为什么使用Roc和Auc评价分类器? 56
2.40.15 直观理解AUC 56
2.40.16 代价敏感错误率与代价曲线 57
2.40.17 模型有哪些比较检验方法 59
2.40.18 偏差与方差 59
2.40.19 为什么使用标准差? 60
2.40.20 点估计思想 61
2.40.21 点估计优良性原则? 61
2.40.22 点估计、区间估计、中心极限定理之间的联系? 62
2.40.23 类别不平衡产生原因? 62
2.40.24 常见的类别不平衡问题解决方法 62
2.41 决策树 64
2.41.1 决策树的基本原理 64
2.41.2 决策树的三要素? 64
2.41.3 决策树学习基本算法 65
2.41.4 决策树算法优缺点 65
2.40.5 熵的概念以及理解 66
2.40.6 信息增益的理解 66
2.40.7 剪枝处理的作用及策略? 67
2.41 支持向量机 67
2.41.1 什么是支持向量机 67
2.25.2 支持向量机解决的问题? 68
2.25.2 核函数作用? 69
2.25.3 对偶问题 69
2.25.4 理解支持向量回归 69
2.25.5 理解SVM(核函数) 69
2.25.6 常见的核函数有哪些? 69
2.25.6 软间隔与正则化 73
2.25.7 SVM主要特点及缺点? 73
2.26 贝叶斯 74
2.26.1 图解极大似然估计 74
2.26.2 朴素贝叶斯分类器和一般的贝叶斯分类器有什么区别? 76
2.26.4 朴素与半朴素贝叶斯分类器 76
2.26.5 贝叶斯网三种典型结构 76
2.26.6 什么是贝叶斯错误率 76
2.26.7 什么是贝叶斯最优错误率 76
2.27 EM算法解决问题及实现流程 76
2.28 为什么会产生维数灾难? 78
2.29 怎样避免维数灾难 82
2.30 聚类和降维有什么区别与联系? 82
2.31 GBDT和随机森林的区别 83
2.32 四种聚类方法之比较 84

第三章 深度学习基础 88

3.1 基本概念 88
3.1.1 神经网络组成? 88
3.1.2 神经网络有哪些常用模型结构? 90
3.1.3 如何选择深度学习开发平台? 92
3.1.4 为什么使用深层表示 92
3.1.5 为什么深层神经网络难以训练? 93
3.1.6 深度学习和机器学习有什么不同 94
3.2 网络操作与计算 95
3.2.1 前向传播与反向传播? 95
3.2.2 如何计算神经网络的输出? 97
3.2.3 如何计算卷积神经网络输出值? 98
3.2.4 如何计算Pooling层输出值输出值? 101
3.2.5 实例理解反向传播 102
3.3 超参数 105
3.3.1 什么是超参数? 105
3.3.2 如何寻找超参数的最优值? 105
3.3.3 超参数搜索一般过程? 106
3.4 激活函数 106
3.4.1 为什么需要非线性激活函数? 106
3.4.2 常见的激活函数及图像 107
3.4.3 常见激活函数的导数计算? 109
3.4.4 激活函数有哪些性质? 110
3.4.5 如何选择激活函数? 110
3.4.6 使用ReLu激活函数的优点? 111
3.4.7 什么时候可以用线性激活函数? 111
3.4.8 怎样理解Relu(<0时)是非线性激活函数? 111
3.4.9 Softmax函数如何应用于多分类? 112
3.5 Batch_Size 113
3.5.1 为什么需要Batch_Size? 113
3.5.2 Batch_Size值的选择 114
3.5.3 在合理范围内,增大 Batch_Size 有何好处? 114
3.5.4 盲目增大 Batch_Size 有何坏处? 114
3.5.5 调节 Batch_Size 对训练效果影响到底如何? 114
3.6 归一化 115
3.6.1 归一化含义? 115
3.6.2 为什么要归一化 115
3.6.3 为什么归一化能提高求解最优解速度? 115
3.6.4 3D图解未归一化 116
3.6.5 归一化有哪些类型? 117
3.6.6 局部响应归一化作用 117
3.6.7 理解局部响应归一化公式 117
3.6.8 什么是批归一化(Batch Normalization) 118
3.6.9 批归一化(BN)算法的优点 119
3.6.10 批归一化(BN)算法流程 119
3.6.11 批归一化和群组归一化 120
3.6.12 Weight Normalization和Batch Normalization 120
3.7 预训练与微调(fine tuning) 121
3.7.1 为什么无监督预训练可以帮助深度学习? 121
3.7.2 什么是模型微调fine tuning 121
3.7.3 微调时候网络参数是否更新? 122
3.7.4 fine-tuning模型的三种状态 122
3.8 权重偏差初始化 122
3.8.1 全都初始化为0 122
3.8.2 全都初始化为同样的值 123
3.8.3 初始化为小的随机数 124
3.8.4 用1/sqrt(n)校准方差 125
3.8.5 稀疏初始化(Sparse Initialazation) 125
3.8.6 初始化偏差 125
3.9 Softmax 126
3.9.1 Softmax定义及作用 126
3.9.2 Softmax推导 126
3.10 理解One Hot Encodeing原理及作用? 126
3.11 常用的优化器有哪些 127
3.12 Dropout 系列问题 128
3.12.1 dropout率的选择 128
3.27 Padding 系列问题 128

第四章 经典网络 129

4.1 LetNet5 129
4.1.1 模型结构 129
4.1.2 模型结构 129
4.1.3 模型特性 131
4.2 AlexNet 131
4.2.1 模型结构 131
4.2.2 模型解读 131
4.2.3 模型特性 135
4.3 可视化ZFNet-解卷积 135
4.3.1 基本的思想及其过程 135
4.3.2 卷积与解卷积 136
4.3.3 卷积可视化 137
4.3.4 ZFNe和AlexNet比较 139
4.4 VGG 140
4.1.1 模型结构 140
4.1.2 模型特点 140
4.5 Network in Network 141
4.5.1 模型结构 141
4.5.2 模型创新点 141
4.6 GoogleNet 143
4.6.1 模型结构 143
4.6.2 Inception 结构 145
4.6.3 模型层次关系 146
4.7 Inception 系列 148
4.7.1 Inception v1 148
4.7.2 Inception v2 150
4.7.3 Inception v3 153
4.7.4 Inception V4 155
4.7.5 Inception-ResNet-v2 157
4.8 ResNet及其变体 158
4.8.1 重新审视ResNet 159
4.8.2 残差块 160
4.8.3 ResNet架构 162
4.8.4 残差块的变体 162
4.8.5 ResNeXt 162
4.8.6 Densely Connected CNN 164
4.8.7 ResNet作为小型网络的组合 165
4.8.8 ResNet中路径的特点 166
4.9 为什么现在的CNN模型都是在GoogleNet、VGGNet或者AlexNet上调整的? 167

第五章 卷积神经网络(CNN) 170

5.1 卷积神经网络的组成层 170
5.2 卷积如何检测边缘信息? 171
5.2 卷积的几个基本定义? 174
5.2.1 卷积核大小 174
5.2.2 卷积核的步长 174
5.2.3 边缘填充 174
5.2.4 输入和输出通道 174
5.3 卷积网络类型分类? 174
5.3.1 普通卷积 174
5.3.2 扩张卷积 175
5.3.3 转置卷积 176
5.3.4 可分离卷积 177
5.3 图解12种不同类型的2D卷积? 178
5.4 2D卷积与3D卷积有什么区别? 181
5.4.1 2D 卷积 181
5.4.2 3D卷积 182
5.5 有哪些池化方法? 183
5.5.1 一般池化(General Pooling) 183
5.5.2 重叠池化(OverlappingPooling) 184
5.5.3 空金字塔池化(Spatial Pyramid Pooling) 184
5.6 1x1卷积作用? 186
5.7 卷积层和池化层有什么区别?  187
5.8 卷积核一定越大越好? 189
5.9 每层卷积只能用一种尺寸的卷积核? 189
5.10 怎样才能减少卷积层参数量? 190
5.11卷积操作时必须同时考虑通道和区域吗? 191
5.12 采用宽卷积的好处有什么?  192
5.12.1 窄卷积和宽卷积 192
5.12.2 为什么采用宽卷积? 192
5.13 卷积层输出的深度与哪个部件的个数相同?  192
5.14 如何得到卷积层输出的深度? 193
5.15 激活函数通常放在卷积神经网络的那个操作之后?  194
5.16 如何理解最大池化层有几分缩小? 194
5.17 理解图像卷积与反卷积 194
5.17.1 图像卷积 194
5.17.2 图像反卷积 196
5.18 不同卷积后图像大小计算? 198
5.18.1 类型划分 198
5.18.2 计算公式 199
5.19 步长、填充大小与输入输出关系总结? 199
5.19.1 没有0填充,单位步长 200
5.19.2 零填充,单位步长 200
5.19.3 不填充,非单位步长 202
5.19.4 零填充,非单位步长 202
5.20 理解反卷积和棋盘效应 204
5.20.1 为什么出现棋盘现象? 204
5.20.2 有哪些方法可以避免棋盘效应? 205
5.21 CNN主要的计算瓶颈? 207
5.22 CNN的参数经验设置 207
5.23 提高泛化能力的方法总结 208
5.23.1 主要方法 208
5.23.2 实验证明 208
5.24 CNN在CV与NLP领域运用的联系与区别? 213
5.24.1 联系 213
5.24.2 区别 213
5.25 CNN凸显共性的手段? 213
5.25.1 局部连接 213
5.25.2 权值共享 214
5.25.3 池化操作 215
5.26 全卷积与Local-Conv的异同点 215
5.27 举例理解Local-Conv的作用 215
5.28 简述卷积神经网络进化史 216

第六章 循环神经网络(RNN) 218

6.1 RNNs和FNNs有什么区别? 218
6.2 RNNs典型特点? 218
6.3 RNNs能干什么? 219
6.4 RNNs在NLP中典型应用? 220
6.5 RNNs训练和传统ANN训练异同点? 220
6.6 常见的RNNs扩展和改进模型 221
6.6.1 Simple RNNs(SRNs) 221
6.6.2 Bidirectional RNNs 221
6.6.3 Deep(Bidirectional) RNNs 222
6.6.4 Echo State Networks(ESNs) 222
6.6.5 Gated Recurrent Unit Recurrent Neural Networks 224
6.6.6 LSTM Netwoorks 224
6.6.7 Clockwork RNNs(CW-RNNs) 225

第七章 目标检测 228

7.1 基于候选区域的目标检测器 228
7.1.1 滑动窗口检测器 228
7.1.2 选择性搜索 229
7.1.3 R-CNN 230
7.1.4 边界框回归器 230
7.1.5 Fast R-CNN 231
7.1.6 ROI 池化 233
7.1.7 Faster R-CNN 233
7.1.8 候选区域网络 234
7.1.9 R-CNN 方法的性能 236
7.2 基于区域的全卷积神经网络(R-FCN) 237
7.3 单次目标检测器 240
7.3.1单次检测器 241
7.3.2 滑动窗口进行预测 241
7.3.3 SSD 243
7.4 YOLO系列 244
7.4.1 YOLOv1介绍 244
7.4.2 YOLOv1模型优缺点? 252
7.4.3 YOLOv2 253
7.4.4 YOLOv2改进策略 254
7.4.5 YOLOv2的训练 261
7.4.6 YOLO9000 261
7.4.7 YOLOv3 263
7.4.8 YOLOv3改进 264

第八章 图像分割 269

8.1 传统的基于CNN的分割方法缺点? 269
8.1 FCN 269
8.1.1 FCN改变了什么? 269
8.1.2 FCN网络结构? 270
8.1.3 全卷积网络举例? 271
8.1.4 为什么CNN对像素级别的分类很难? 271
8.1.5 全连接层和卷积层如何相互转化? 272
8.1.6 FCN的输入图片为什么可以是任意大小? 272
8.1.7 把全连接层的权重W重塑成卷积层的滤波器有什么好处? 273
8.1.8 反卷积层理解 275
8.1.9 跳级(skip)结构 276
8.1.10 模型训练 277
8.1.11 FCN缺点 280
8.2 U-Net 280
8.3 SegNet 282
8.4 空洞卷积(Dilated Convolutions) 283
8.4 RefineNet 285
8.5 PSPNet 286
8.6 DeepLab系列 288
8.6.1 DeepLabv1 288
8.6.2 DeepLabv2 289
8.6.3 DeepLabv3 289
8.6.4 DeepLabv3+ 290
8.7 Mask-R-CNN 293
8.7.1 Mask-RCNN 的网络结构示意图 293
8.7.2 RCNN行人检测框架 293
8.7.3 Mask-RCNN 技术要点 294
8.8 CNN在基于弱监督学习的图像分割中的应用 295
8.8.1 Scribble标记 295
8.8.2 图像级别标记 297
8.8.3 DeepLab+bounding box+image-level labels 298
8.8.4 统一的框架 299

第九章 强化学习 301

9.1 强化学习的主要特点? 301
9.2 强化学习应用实例 302
9.3 强化学习和监督式学习、非监督式学习的区别 303
9.4 强化学习主要有哪些算法? 305
9.5 深度迁移强化学习算法 305
9.6 分层深度强化学习算法 306
9.7 深度记忆强化学习算法 306
9.8 多智能体深度强化学习算法 307
9.9 深度强化学习算法小结 307

第十章 迁移学习 309

10.1 什么是迁移学习? 309
10.2 什么是多任务学习? 309
10.3 多任务学习有什么意义? 309
10.4 什么是端到端的深度学习? 311
10.5 端到端的深度学习举例? 311
10.6 端到端的深度学习有什么挑战? 311
10.7 端到端的深度学习优缺点? 312

第十三章 优化算法 314

13.1 CPU和GPU 的区别? 314
13.2 如何解决训练样本少的问题 315
13.3 什么样的样本集不适合用深度学习? 315
13.4 有没有可能找到比已知算法更好的算法? 316
13.5 何为共线性, 跟过拟合有啥关联? 316
13.6 广义线性模型是怎被应用在深度学习中? 316
13.7 造成梯度消失的原因? 317
13.8 权值初始化方法有哪些 317
13.9 启发式优化算法中,如何避免陷入局部最优解? 318
13.10 凸优化中如何改进GD方法以防止陷入局部最优解 319
13.11 常见的损失函数? 319
13.14 如何进行特征选择(feature selection)? 321
13.14.1 如何考虑特征选择 321
13.14.2 特征选择方法分类 321
13.14.3 特征选择目的 322
13.15 梯度消失/梯度爆炸原因,以及解决方法 322
13.15.1 为什么要使用梯度更新规则? 322
13.15.2 梯度消失、爆炸原因? 323
13.15.3 梯度消失、爆炸的解决方案 324
13.16 深度学习为什么不用二阶优化 325
13.17 怎样优化你的深度学习系统? 326
13.18为什么要设置单一数字评估指标? 326
13.19满足和优化指标(Satisficing and optimizing metrics) 327
13.20 怎样划分训练/开发/测试集 328
13.21如何划分开发/测试集大小 329
13.22什么时候该改变开发/测试集和指标? 329
13.23 设置评估指标的意义? 330
13.24 什么是可避免偏差? 331
13.25 什么是TOP5错误率? 331
13.26 什么是人类水平错误率? 332
13.27 可避免偏差、几大错误率之间的关系? 332
13.28 怎样选取可避免偏差及贝叶斯错误率? 332
13.29 怎样减少方差? 333
13.30 贝叶斯错误率的最佳估计 333
13.31 举机器学习超过单个人类表现几个例子? 334
13.32 如何改善你的模型? 334
13.33 理解误差分析 335
13.34 为什么值得花时间查看错误标记数据? 336
13.35 快速搭建初始系统的意义? 336
13.36 为什么要在不同的划分上训练及测试? 337
13.37 如何解决数据不匹配问题? 338
13.38 梯度检验注意事项? 340
13.39 什么是随机梯度下降? 341
13.40 什么是批量梯度下降? 341
13.41 什么是小批量梯度下降? 341
13.42 怎么配置mini-batch梯度下降 342
13.43 局部最优的问题 343
13.44 提升算法性能思路 346

第十四章 超参数调整 358

14.1 调试处理 358
14.2 有哪些超参数 359
14.3 如何选择调试值? 359
14.4 为超参数选择合适的范围 359
14.5 如何搜索超参数? 359

第十五章 异构计算, GPU和框架选型指南 361

15.1 什么是异构计算? 361
15.2 什么是GPGPU? 361
15.3 GPU架构简介 361
15.3.1 为什么要使用GPU?
15.3.2 CUDA 核心是什么?
15.3.3 新图灵架构里的tensor core对深度学习有什么作用?
15.3.4 GPU内存架构和应用性能的联系?
15.4 CUDA 框架
15.4.1 做CUDA编程难不难?
15.4.2 cuDNN
15.5 GPU硬件环境配置推荐
15.5.1 GPU主要性能指标
15.5.2 购买建议
15.6 软件环境搭建
15.6.1 操作系统选择?
15.6.2 本机安装还是使用docker?
15.6.3 GPU驱动问题
15.7 框架选择
15.7.1 主流框架比较
15.7.2 框架详细信息
15.7.3 哪些框架对于部署环境友好?
15.7.4 移动平台的框架如何选择?
15.8 其他
15.8.1 多GPU环境的配置
15.8.2 是不是可以分布式训练?
15.8.3 可以在SPARK环境里训练或者部署模型吗?
15.8.4 怎么进一步优化性能?
15.8.5 TPU和GPU的区别?
15.8.6 未来量子计算对于深度学习等AI技术的影响?

参考文献 366

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