The Artificial Intelligence Infrastructure Workshop
Chinmay Arankalle Gareth Dwyer Bas Geerdink Kunal Gera Kevin Liao Anand N.S.更新时间：2021-06-11 18:35:51
最新章节：12. Productionizing Your AI Applications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
9. Workflow Management for AI
10. Introduction to Data Storage on Cloud Services (AWS)
11. Building an Artificial Intelligence Algorithm
12. Productionizing Your AI Applications
更新时间：2021-06-11 18:35:51