Analyzing and Visualizing Data with F#

Table of contents

1. Acknowledgements
2. 1. Accessing Data with Type Providers
   1. Data Science Workflow
   2. Why Choose F# for Data Science?
   3. Getting Data from the World Bank
   4. Calling the Open Weather Map REST API
   5. Plotting Temperatures Around the World
   6. Conclusions
3. 2. Analyzing Data Using F# and Deedle
   1. Downloading Data Using an XML Provider
   2. Visualizing CO2 Emissions Change
   3. Aligning and Summarizing Data with Frames
   4. Summarizing Data Using the R Provider
   5. Normalizing the World Data Set
   6. Conclusions
4. 3. Implementing Machine Learning Algorithms
   1. How k-Means Clustering Works
   2. Clustering 2D Points
   3. Initializing Centroids and Clusters
   4. Updating Clusters Recursively
   5. Writing a Reusable Clustering Function
   6. Clustering Countries
   7. Scaling to the Cloud with MBrace
   8. Conclusions
5. 4. Conclusions and Next Steps
   1. Adding F# to Your Project
   2. Resources for Learning More