Data Engineering Handbook
Data Engineering Handbook
Build durable, scalable, orchestrated software in Go with Kubernetes
About the Book
Chapters:
- Introduction to Machine Learning (ML) and Data Science
- Unit Testing and Test Driven Development Methodologies
- Data-intensive APIs Using a RESTful Approach
- Designing and Developing Distributed Systems
- Data Ingress from IoT Devices
- Stream Processing Using Apache Kafka
- Interacting with SQS Topics
- Creating and Maintaining Containerized Application Deployments
- Building and Maintaining a Cloud Based Infrastructure
- Securing Deployments and Cloud-Ops
- Continuous Integration and Continuous Delivery
- Deploying and Maintaining K8s on AWS and GCP
- Google Cloud Dataflow SDK on Apache Beam
- Applying Resource-Oriented Design Concepts
- Creating Machine Learning (ML) Platforms
- Building Analytical Pipelines
- Big Data Algorithms and Data Structures
- Analyzing Data with Python and R
- Application of Quantitative Science to Solve Business Problems
- Deep Data Analysis
- Prometheus, Grafana, and other Application Monitoring Tools
- Developing Kubeflow Solutions in Go
- Where To Go From Here
About the Author
Table of Contents
- Preface (DRAFT)
-
1 Intro to Data Science and Machine Learning (DRAFT)
- Data Science
- Data Science Modeling
- Machine Learning
- Data Science
- Data Scientists
- 2 Unit Testing and Test Driven Development Methodologies
- 3 Data-intensive APIs Using a RESTful Approach
- 4 Designing and Developing Distributed Systems
- 5 Data Ingress from IoT Devices
- 6 Stream Processing Using Apache Kafka
- 7 Interacting with the SQS Distributed Queuing System
- 10 Securing Deployments and Cloud-Ops
- 11 Continuous Integration and Continuous Delivery
- 13 Google Cloud Dataflow SDK on Apache Beam
- 14 Applying Resource-Oriented Design Concepts
- 15 Creating Machine Learning (ML) Platforms
- 16 Building Analytical Pipelines
- 17 Big Data Algorithms and Data Structures
- 18 Analyzing Data with Python and R
- 19 Application of Quantitative Science to Solve Business Problems
- 20 Prometheus, Grafana, and other Application Monitoring Tools
- 21 Develop Kubeflow Solutions in Go
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