Michał J Gajda is a bioinformatician turned data scientist, turned banker, turned software startup founder. He loves to mix the best of science and programming methodology into tasty dishes of ultimate utility.
Michał J Gajda is a bioinformatician turned data scientist, turned banker, turned software startup founder. He loves to mix the best of science and programming methodology into tasty dishes of ultimate utility.
Talks I've Given
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Live Coding a Roguelike Game
Featuring Michał J. Gajda
Michal J Gajda shares a simple way to do live coding and event sourcing for the development of a game using Haskell. This method is the product of a long effort to reduce the effort and complexity of debugging and writing interactive software, and it is recommended for all Haskell beginners!
software-development event-sourcing game-development roguelike haskell -
Live Coding a Roguelike Game
Featuring Michał J. Gajda
Michal J Gajda shares a simple way to do live coding and event sourcing for the development of a game using Haskell. This method is the product of a long effort to reduce the effort and complexity of debugging and writing interactive software, and it is recommended for all Haskell beginners!
software-development event-sourcing roguelike game-development haskell -
Agile Functional Data Pipeline in Haskell: A Case Study of Multicloud API Binding
Featuring Michał J. Gajda
In this case study, Michał discusses making a data pipeline for multicloud API bindings in Haskell for analysis and Python for scraping. He'll introduce a few rules settled on along the way that allow for blinding fast development of agile data analytics.
haskell data-analytics case-study python api-binding multicloud -
Lightning Talk: Making and Testing Code Generators in Haskell
Featuring Michał J. Gajda
Michał and the Migamake Pte Ltd team are currently making an open source library to help produce code generators in Haskell. It facilitates generating code with syntax-checked templates and unit testing with smaller and more robust tests Michał will go through code generation approaches seen in...
haskell generators -
Automating Elaborate-Transform-Load for Busy Data Scientists
Featuring Michał J. Gajda
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....
data haskell parsing csv etl metadata ingest xml json bigdata analytics datascience