Book description
In many companies today, discussions about predictive analytics and machine learning tend to overlook one critical component: implementation. This report will help you examine practical methods for building and deploying scalable, production-ready machine-learning applications. Leveraging machine-learning models in production, after all, separates revenue generation and cost savings from mere intellectual novelty.
Product specialists from MemSQL describe several real-time use cases, including "operational" applications, where machine-learning models automate decision-making processes, as well as "interactive" applications, where machine learning informs decisions made by humans. You’ll also explore modern data processing architectures and leading technologies available for data processing, analysis, and visualization.
With this report, you’ll find ways to:
- Build real-time data pipelines
- Process transactions and analytics in a single database
- Create custom real-time dashboards
- Redeploy batch models in real time
- Build real-time machine learning applications
- Prepare data pipelines for predictive analytics and machine learning
- Apply predictive analytics to real-time challenges
- Use techniques for predictive analytics in production
- Move from machine learning to artificial intelligence
Table of contents
- Introduction
- 1. Building Real-Time Data Pipelines
- 2. Processing Transactions and Analytics in a Single Database
- 3. Dawn of the Real-Time Dashboard
- 4. Redeploying Batch Models in Real Time
- 5. Applied Introduction to Machine Learning
- 6. Real-Time Machine Learning Applications
- 7. Preparing Data Pipelines for Predictive Analytics and Machine Learning
- 8. Predictive Analytics in Use
- 9. Techniques for Predictive Analytics in Production
- 10. From Machine Learning to Artificial Intelligence
- A. Appendix
Product information
- Title: The Path to Predictive Analytics and Machine Learning
- Author(s):
- Release date: October 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491969687
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