The Artificial Intelligence Infrastructure Workshop

封面

版权信息

Preface

1. Data Storage Fundamentals

Introduction

Problems Solved by Machine Learning

Optimizing the Storing and Processing of Data for Machine Learning Problems

Diving into Text Classification

Looking at Terminology in Text Classification Tasks

Designing for Scale – Choosing the Right Architecture and Hardware

Using Vectorized Operations to Analyze Data Fast

Summary

2. Artificial Intelligence Storage Requirements

Introduction

Storage Requirements

Data Layers

Raw Data

Historical Data

Streaming Data

Analytics Data

Model Development and Training

Summary

3. Data Preparation

Introduction

ETL

Data Processing Techniques

Streaming Data

Summary

4. The Ethics of AI Data Storage

Introduction

Summary

5. Data Stores: SQL and NoSQL Databases

Introduction

Database Components

SQL Databases

MySQL

NoSQL Databases

MongoDB

Cassandra

Exploring the Collective Knowledge of Databases

Summary

6. Big Data File Formats

Introduction

Common Input Files

Choosing the Right Format for Your Data

Introduction to File Formats

Summary

7. Introduction to Analytics Engine (Spark) for Big Data

Introduction

Apache Spark

Apache Spark and Databricks

Understanding Various Spark Transformations

Understanding Various Spark Actions

Best Practices

Summary

8. Data System Design Examples

Introduction

The Importance of System Design

Components to Consider in System Design

Examining a Pipeline Design for an AI System

Making a Pipeline System Highly Available

Summary

9. Workflow Management for AI

Introduction

Creating Your Data Pipeline

Challenges in Managing Processes in the Real World

Automating a Data Pipeline

Automating Asynchronous Data Pipelines

Workflow Management with Airflow

Summary

10. Introduction to Data Storage on Cloud Services (AWS)

Introduction

Interacting with Cloud Storage

Getting Started with Cloud Relational Databases

Introduction to NoSQL Data Stores on the Cloud

Data in Document Format

Summary

11. Building an Artificial Intelligence Algorithm

Introduction

Machine Learning Algorithms

Model Training

Gradient Descent

Getting Started with PyTorch

Mini-Batch SGD with PyTorch

Summary

12. Productionizing Your AI Applications

Introduction

pickle and Flask

Deploying Models to Production

Model Execution in Streaming Data Applications

Summary

Appendix

1. Data Storage Fundamentals

2. Artificial Intelligence Storage Requirements

3. Data Preparation

4. Ethics of AI Data Storage

5. Data Stores: SQL and NoSQL Databases

6. Big Data File Formats

7. Introduction to Analytics Engine (Spark) for Big Data

8. Data System Design Examples