### Data Science / Machine Learning / Deep Learning 2017

- Time series shootout: ARIMA vs. LSTM

Presentation, github - Automatic Crack Detection – with Deep Learning

Presentation, github - Variational autoencoders for anomaly detection (Talk at Trivadis Tech Event 09/2017)

Presentation, github - Deep learning in action – with DL4J (Talk at Trivadis Tech Event 09/2017)

pdf, github - Haskell, R, HaskellR: Combining the best of both worlds (Talk at UseR!2017)

Presentation

Intro to HaskellR (IHaskell notebook)

Stockmarket demo (IHaskell notebook) - Time series prediction – with Deep Learning

RPubs, pdf, github - Deep Learning in Action – the “less math, more applications” version

RPubs, pdf, github - R for hackers

RPubs, pdf, github

### Data Science / Machine Learning / Deep Learning 2016

- Deep Learning in Action

nbviewer, github, pdf - R for SQListas – a Continuation

RPubs, pdf, github - R for SQListas (DOAG 2016)

RPubs, pdf, github - A Sentimental Journey: Sentiment Analysis of Movie Reviews (Trivadis Tech Event, September 2016)

nbviewer, pdf, github, en français (nbviewer), en français (pdf), en français (github)

### Other

- Tune the App, Not the SQL – DBA Sherlock’s Adventures in Hibernate/jOOQ Land (Trivadis Tech Event, February 2016)
- Application Continuity, Transaction Guard … choose your degrees of freedom! (Trivadis Tech Event, February 2016)
- Object Relational Mapping Tools – Let’s Talk to Each Other! (Trivadis Tech Event, September 2015)
- Raising the Fetch Size, Good or Bad? Memory Management in Oracle JDBC 12c (DOAG 2015)

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