Doing data science with F#
Tomas Petricek
tomas@tomasp.net | @tomaspetricek
PhD Student at Cambridge & Coordinator of http...
software stacks

trainings
mac and linux

teaching F#

user groups

snippets

community books and tutorials

F# Software F...
Community matters!
All the Data of the World
data acquisition

statistics data cleaning machine learning
data transformation

visualization type providers

F# Data Sci...
Acquire

Visualize

Analyze
Demo: Analyzing Titanic survivors
Deedle data frame
Data exploration
Indexing and aggregation

F# Charting library
Simple & composable
Interactive style

ww...
Demo: Understanding the world
F# Data type providers
First-class data
CSV, REST, WorldBank…

R Type provider
Statistics & visualization
5000 tested pack...
Demo: US debt over the last century
Deedle data frame
Time-series alignment
Data transformations

Vega visualization
F# wrapper for Vega
Pre-alpha version

ww...
F# for Data Science
acquire, analyze, visualize
interactive experience
safety and efficiency of .net
ready for production
...
Going forward
Use #fsharp for fun & profit
Join local user groups
Help us build data science tools
fsharp.org | fslab.org ...
Upcoming SlideShare
Loading in...5
×

Doing data science with F#

901

Published on

The ability to take data, understand it, visualize it and extract useful information from it is becoming a hugely important skill. How can you turn all those logs, histories of purchases and trades or open government data, into useful information that help your business make money?

In this talk, we’ll look at doing data science using F#. The F# language is perfectly suited for this task – type providers integrate external data directly into the language – your language suddenly _understands_ CSV, XML, JSON, REST services and other sources. The interactive development style makes it easy to explore data and test your algorithms as you’re writing them. Rich set of libraries for working with data frames, time series and for visualization gives you all the tools you need. And finally – F# easily integrates with statistical environments like R and Matlab, giving you access to the industry standard libraries.

Published in: Technology, Education
0 Comments
1 Like
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
901
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
8
Comments
0
Likes
1
Embeds 0
No embeds

No notes for slide

Doing data science with F#

  1. 1. Doing data science with F# Tomas Petricek tomas@tomasp.net | @tomaspetricek PhD Student at Cambridge & Coordinator of http://fsharp.org
  2. 2. software stacks trainings mac and linux teaching F# user groups snippets community books and tutorials F# Software Foundation consulting open-source MonoDevelop http://www.fsharp.org contributions research support cross-platform mailing lists
  3. 3. Community matters!
  4. 4. All the Data of the World
  5. 5. data acquisition statistics data cleaning machine learning data transformation visualization type providers F# Data Science Working Group kaggle vega grammar R provider data sources presentation www.fslab.org time-series visualization data aggregation
  6. 6. Acquire Visualize Analyze
  7. 7. Demo: Analyzing Titanic survivors
  8. 8. Deedle data frame Data exploration Indexing and aggregation F# Charting library Simple & composable Interactive style www.fslab.org
  9. 9. Demo: Understanding the world
  10. 10. F# Data type providers First-class data CSV, REST, WorldBank… R Type provider Statistics & visualization 5000 tested packages www.fslab.org
  11. 11. Demo: US debt over the last century
  12. 12. Deedle data frame Time-series alignment Data transformations Vega visualization F# wrapper for Vega Pre-alpha version www.fslab.org
  13. 13. F# for Data Science acquire, analyze, visualize interactive experience safety and efficiency of .net ready for production @tomaspetricek
  14. 14. Going forward Use #fsharp for fun & profit Join local user groups Help us build data science tools fsharp.org | fslab.org | tomasp.net @tomaspetricek
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×