Talk given at Strata London with Dean Wampler (Lightbend) about Scala as the future of Data Science. First part is an approach of how scala became important, the remaining part of the talk is in notebooks using the Spark Notebook (http://spark-notebook.io/). The notebooks are available on GitHub: https://github.com/data-fellas/scala-for-data-science.

1. Scala:
the Unpredicted lingua franca
for Data Science
Dean Wampler
@deanwampler
lightbend
Andy Petrella
@noootsab
Data Fellas

2. Distributed Data Science
Distributed Data Science is
the “new” interpretation of “big data”

3. Big Data
Why Distributed Computing became Big Data?

4. Big Data was the visible part of the Iceberg
Business
Thanks @Google(for All the fish)

5. Enterprise ready Open Source Implementation
Hadoop (JVM -- Enterprise)

6. Big Data made easy → it becomes popular
Spark (Scala -- Functional)

7. After the How, the what
Distributed Data Science

8. WhyScala.snb
https://github.com/data-fellas/scala-for-data-science
Scala features for data science

9. Tooling, port models AND invent new models!
What’s missing in Scala/JVM?

10. Why Spark Notebook.snb
https://github.com/data-fellas/scala-for-data-science
Tooling for data science

11. No more one-liner...
● MLlib (and other AMPLab stuff: MLPipeline, MLBase)
● Deeplearning4J
● OptiML
● Streaming Clustering: G-Stream, Mean-Shift-LSH, SOM-MR
● Figaro
Universities are now teaching for data science
● LIPN
● Radboud Universiteit (http://rubigdata.github.io/course/)
Education: Data Science Inc. (12 weeks!)
Of course, check http://spark-packages.org
Models and education(soon snb)

12. Scala:
the Unpredicted lingua franca
for Data Science
Dean Wampler
@deanwampler
lightbend
Andy Petrella
@noootsab
Data Fellas