There are far too many AWS services to cover in one section. We will cover the ones of interest for IoT analytics but know that there are many more with new services being added all the time (such as speech recognition and deep learning image recognition services).
- Preface
- Defining IoT Analytics and Challenges
- IoT Devices and Networking Protocols
- IoT devices
- Networking basics
- IoT networking connectivity protocols
- IoT networking data messaging protocols
- Analyzing data to infer protocol and device characteristics
- Summary
- IoT Analytics for the Cloud
- Creating an AWS Cloud Analytics Environment
- Collecting All That Data - Strategies and Techniques
- Getting to Know Your Data - Exploring IoT Data
- Exploring and visualizing data
- Look for attributes that might have predictive value
- R (the pirate's language...if he was a statistician)
- Summing it all up
- Solving industry-specific analysis problems
- Summary
- Decorating Your Data - Adding External Datasets to Innovate
- Communicating with Others - Visualization and Dashboarding
- Applying Geospatial Analytics to IoT Data
- Data Science for IoT Analytics
- Machine learning (ML)
- Anomaly detection using R
- Forecasting using ARIMA
- Deep learning
- Summary
- Strategies to Organize Data for Analytics
- The Economics of IoT Analytics
- Bringing It All Together
AWS key services for IoT analytics
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