Building Intelligent Cloud Applications Develop Scalable Models Using Serverless Architectures with Azure 1st Edition by Vicente Herrera García, John Biggs ISBN 1492052329 978-1492052326

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Product details:

ISBN 10: 1492052329 

ISBN 13: 978-1492052326

Author: Vicente Herrera García, John Biggs

Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing machine resources, companies now can focus solely on the application’s business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure.

You’ll learn step-by-step how to code machine learning into your projects using Python and pretrained models that include tools such as image recognition, speech recognition, and classification. You’ll also examine issues around deployment and continuous delivery, including scaling, security, and monitoring.

Table of contents: 

I. Cloud-Based Development

1. Machine Learning and Deep Learning Models in the Cloud

1. An Introduction to Machine Learning
2. An Introduction to Deep Learning
3. Neural Networks
4. Difficulties Defining Structure and Training Machine Learning Models
5. An Introduction to Serverless Machine Learning
6. Using Containers with Machine Learning Models
7. The Benefits of Serverless Computing for Machine Learning

2. Functions-as-a-Service and Event-Driven Programming

1. Software-as-a-Service, Cloud Computing, and Serverless
2. Microservices Architecture
3. The Rise of Functional Programming
4. Using Functions Instead of Objects
5. Asynchronous Programming
6. Serverless
7. Implementing Functions
8. Event-Driven Architecture
9. Implications of Real-Time Processing
10. Summary and Look Ahead

3. Serverless Application Programming Interfaces in Microsoft Azure

1. APIs in Serverless Platforms
2. An Introduction to Azure
3. Azure General Services

II. Adding Intelligence

4. Getting Started with Microsoft Azure Functions

1. Azure Functions
2. Creating a Function App by Using Azure Portal
3. Local Development Environment
4. Creating a Functions Project Using Core Tools
5. Using Visual Studio Code
6. Debugging Python by Using Visual Studio Code
7. Azure Blob Storage
8. Creating a Storage Account
9. Transferring Blobs
10. Summary and Look Ahead

5. Using Machine Learning and Deep Learning Models

1. Azure Cognitive Services
2. Setting Up and Using a Service in Cognitive Services
3. Using a Cognitive Service from a Serverless Azure Functions Project
4. General Machine Learning Tools, Libraries, and Frameworks
5. Microsoft Cognitive Toolkit
6. ML.NET
7. Jupyter Notebook
8. TensorFlow
9. Keras
10. Scikit-learn
11. Cloud Machine Learning Solutions with Azure
12. Microsoft Machine Learning Studio
13. Azure Machine Learning Service

III. Deployment and Continuous Delivery

6. Deployment and Scaling

1. Deployment Options
2. Azure DevOps
3. Docker
4. Azure Container Registry
5. Kubernetes
6. Machine Learning Tools for Kubernetes
7. Single-Container Machine Learning
8. Distributed Machine Learning with TFJob

7. Security

1. Azure Functions Authorization Levels
2. API Management
3. Azure Security
4. Operations
5. Applications
6. Storage
7. Network Layer Controls
8. Networking

8. Monitoring

1. Azure Monitor
2. Metrics and Logs
3. Data Sources
4. Application Insights
5. Insights for Containers (and VMs)
6. Log Analytics
7. Data Explorer Query Language
8. Alerts
9. Smart Groups
10. Autoscale and Metrics Alerts

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Tags: Vicente Herrera García, John Biggs, Building Intelligent, Cloud Applications, Develop Scalable Models, Serverless Architectures