This material contains different quick courses with many examples and solutions in mathematical problems introducing popular technologies used in data analysis in order to solve these problems, this material is aimed to people that are interested in to starting in data science and big data technologies.
About this content
About this material.
The material presented has been developed with free software, the code that the notebooks contain is mostly its own and made for academic and teaching purposes.
Software used during the elaboration of the content:
| Jupyter notebooks | http://jupyter.org/ |  |
| Scala 2.11 | https://www.scala-lang.org/ |  |
| Docker | https://hub.docker.com/r/jupyter/all-spark-notebook/ |  |
Sklearn contents
| Topic | SubTopic | |
|---|---|---|
| Scala Fundamentals | Introduction to scala | View notebook |
References
Most of the theoretical content is not proper but is a compendium of classic results and examples from of diverse sources.
| "Programming in Scala" | 3rd Edition, Martin Odersky, Lex Spoon, Artima Inc, Canada 2016, ISBN 0981531687.. |
| "Functional Programming in Scala”" | Paul Chiusano, ed. Manning Shelter Island, 2015, ISBN 9781617290657. |
| "Learning Functional Programming in Scala" | https://alvinalexander.com/downloads/learning-fp-in-scala-0.1.1.pdf |
| "Scala Reference Manual" | https://www.scala-lang.org/docu/files/ScalaReference.pdf |