Please log in to watch this conference skillscast.
Haskell is making great strides into processing data at greater convenience. You do not only have fast parsers for most important languages, but now automatic parser generators that discover the structure of our documents and package them as Haskell types: DataFrames, JSON Autotype, XML TypeLift.
Michał will present a tutorial on how to roll your own data ingestion pipeline in fifteen minutes. Then he will dive into a bit of methodology so that the thirsty has a map of materials to look further into.
YOU MAY ALSO LIKE:
- Lightning Talk: Making and Testing Code Generators in Haskell (SkillsCast recorded in October 2019)
- Leonardo De Marchi's Deep Learning Fundamentals (in London on 22nd - 23rd October 2019)
- Brian Sletten's Data Science with Python Workshop (in London on 18th - 20th November 2019)
- Scala eXchange London 2019 (in London on 12th - 13th December 2019)
- Practical ML 2020 (in London on 2nd - 3rd July 2020)
- Reinforcement Learning Journal Club (in London on 17th October 2019)
- Countdown to Big Data LDN (in London on 17th October 2019)
- GHC Runtime Linker by Example (SkillsCast recorded in October 2019)
Automating Elaborate-Transform-Load for Busy Data Scientists
Michał got PhD in structural bioinformatics pipelines, and after two postdocs in top research facilities moved on to use his expertise of data analysis platforms in commerce. After a stint in a bank, and fintech startup, he founded his own company.