Preface Deep learning is a fascinating field. Artificial neural networks have been around for a long time, but something special has happened in recent years. The mixture of new faster hardware, new techniques and highly optimized open source libraries allow very large networks to be created with frightening ease. This new wave of much larger and much deeper neural networks are also impressively skillful on a range of problems. I have watched over recent years as they tackle and handily become state-of-the-art across a range of difficult problem domains. Not least object recognition, speech recognition, sentiment classification, translation and more. When a technique comes a long that does so well on such a broad set of problems, you have to pay attention. The problem is where do you start with deep learning? I created this book because I thought that there was no gentle way for Python machine learning practitioners to quickly get started developing deep learning models. In developing the lessons in this book, I chose the best of breed Python deep learning library called Keras that abstracted away all of the complexity, ruthlessly leaving you an API containing only what you need to know to efficiently develop and evaluate neural network models. This is the guide that I wish I had when I started apply deep learning to machine learning problems. I hope that you find it useful on your own projects and have as much fun applying deep learning as I did in creating this book for you.

对sudo的最详细的解释，是Michael Lucas的经典作品，Lucas也是absolute freebsd等技术图书的作者！

Machine Learning Mastery with Python. Understand your data, create accurate models and work projects end to end

Vue Mastery下载器 注意：此脚本是作为一个周末项目娱乐而制作的，无意伪造视频或进行与Vue Mastery视频相关的任何非法活动。 严格禁止使用下载的视频。 如果您想观看它们，请访问Vue Mastery官方网站！ 如何使用： 克隆此存储库 npm安装 更改example.env中的变量并删除“示例”部分 将您要下载的课程的URL添加到courses.json列表数组中（不包括“ /'first-course-video”部分） 节点index.js 如果出现错误（节点：20857），则UnhandledPromiseRejectionWarning：错误：未下载浏览器。 运行“ npm install”或“ yarn install” ->对于Linux，运行“ sudo npm install puppeteer --unsafe-perm = true --allow

Game Scripting Mastery 中译为：游戏脚本高级编程 我上传的是完整的原版图书哦，而且是文字版！不是笨重的扫描版！ 原PDF为52M，压缩后为15M。 英文原版有助提高英语，同时不必纠结于那些生硬的翻译，一举三得啊！ 下面是简单介绍： 游戏脚本高级编程引领读者进入程序员们称之为“游戏脚本编程”的全新领域，本书将从概括论述什么是脚本编程以及它是如何实现的开始，阐述游戏编程的理念，根据作者多年的开发经验，使读者掌握使用脚本是把游戏代码和主引擎分离开的最理想的办法，带读者进入神秘的游戏脚本语言世界，学习如何编写脚本语言，编译器理论，享受游戏编程方面的极大乐趣。 　　 本书是游戏开发经典丛书系列之一，适合游戏开发人员、业余游戏软件开发爱好者，也可以作为大专院校相关专业的参考书。

Welcome to Machine Learning Algorithms From Scratch. This is your guide to learning the details of machine learning algorithms by implementing them from scratch in Python. You will discover how to load data, evaluate models and implement a suite of top machine learning algorithms using step-by-step tutorials and sample code. Machine learning algorithms do have a lot of math and theory under the covers, but you do not need to know why algorithms work to be able to implement them and apply them to achieve real and valuable results. From an applied perspective, machine learning is a shallow field and a motivated developer can quickly pick it up and start making very real and impactful contributions. This is my goal for you and this book is your ticket to that outcome.

作者以其多年的开发经验带领读者进入神秘的游戏脚本语言世界，学习如何编写脚本语言，编译器理论，享受游戏编程方面的极大乐趣。包含超清晰英文原版pdf以及示例代码。

Preface I think Python is an amazing platform for machine learning. There are so many algorithms and so much power ready to use. I am often asked the question: How do you use Python for machine learning? This book is my definitive answer to that question. It contains my very best knowledge and ideas on how to work through predictive modeling machine learning projects using the Python ecosystem. It is the book that I am also going to use as a refresher at the start of a new project. I’m really proud of this book and I hope that you find it a useful companion on your machine learning journey with Python. Jason Brownlee Melbourne, Australia 2016

将json-server部署到{{ free hosting site }} 说明如何将完整的假REST API 部署到各种免费托管站点。 仅应用于开发目的，但可以将其用作较小应用程序的简单数据库。 创建你的数据库 1。 将此仓库克隆到计算机上的任何位置。 git clone https://github.com/jesperorb/json-server-heroku.git 2。 根据 ，将db.json更改为您自己的内容，然后将更改commit到git。 此示例将创建/posts路由，每个资源将具有id ， title和content 。 id将自动递增！ { " posts " :[ { " id " : 0 , " title " : " First post! " , " content " : " My first c

ZFS improves everything about systems administration. Once you peek under the hood, though, ZFS’ bewildering array of knobs and tunables can overwhelm anyone. ZFS experts can make their servers zing—and now you can, too, with FreeBSD Mastery: Advanced ZFS. This small book teaches you to: • Use boot environments to make the riskiest sysadmin tasks boring • Delegate filesystem privileges to users • Containerize ZFS datasets with jails • Quickly and efficiently replicate data between machines • split layers off of mirrors • optimize ZFS block storage • handle large storage arrays • select caching strategies to improve performance • manage next-generation storage hardware • identify and remove bottlenecks • build screaming fast database storage • dive deep into pools, metaslabs, and more! Whether you manage a single small server or international datacenters, simplify your storage with FreeBSD Mastery: Advanced ZFS. Table of Contents Chapter 0: Introduction Chapter 1: Boot Environments Chapter 2: Delegation and Jails Chapter 3: Sharing Datasets Chapter 4: Replication Chapter 5: ZFS Volumes Chapter 6: Advanced Hardware Chapter 7: Caches Chapter 8: Performance Chapter 9: Tuning Chapter 10: ZFS Potpourri