Fix deleted files

Author: mikebo93

chapter_introduction/index.md

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+# Introduction
+ 
+ This chapter aims to provide readers with a comprehensive understanding
+ of machine learning systems by describing the applications of machine
+ learning and summarizing the design objectives and basic composition
+ principles of such systems.
+ 
+ 
+ ```toc
+ :maxdepth: 2
+ 
+ Machine_Learning_Applications
+ Design_Objectives_of_Machine_Learning_Frameworks
+ Machine_Learning_Framework_Architecture
+ Application_Scenarios_of_Machine_Learning_Systems
+ Book_Organization_and_Intended_Audience
+ ```
+ 

chapter_preface_basic/index.md

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+# Part I Framework Design
+ :label:`part-i-framework-design`
+ 
+ In Part 1, we present a top-down approach to designing a machine
+ learning framework. We begin by introducing the design of programming
+ models for machine learning frameworks, followed by a discussion on
+ representing a machine learning program as a computational graph. The
+ machine learning program undergoes compilation by an AI compiler, which
+ employs a range of frontend and backend techniques. Additionally, we
+ will delve into the system components within a machine learning
+ framework that facilitate data processing, model deployment, and
+ distributed training.
+ 

chapter_preface_extension/index.md

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+# Part II Application Scenarios
+ :label:`part-ii-application-scenarios`
+ 
+ In Part II, we will introduce various scenarios of applying machine
+ learning frameworks. These scenarios include federated learning systems,
+ recommender systems, reinforcement learning systems, and robotic
+ systems.