r (55)
- Why I use R for Data Science - An Ode to R - September 19, 2017
- Explore Predictive Maintenance with flexdashboard - November 2, 2017
- How to combine point and boxplots in timeline charts with ggplot2 facets - November 18, 2017
- Workshop on Deep Learning with Keras and TensorFlow in R - November 20, 2017
- MICE (Multiple Imputation by Chained Equations) in R - sketchnotes from MünsteR Meetup - November 28, 2017
- Explaining Predictions of Machine Learning Models with LIME - Münster Data Science Meetup - December 12, 2017
- Registration now open for workshop on Deep Learning with Keras and TensorFlow using R - December 20, 2017
- How to make your machine learning model available as an API with the plumber package - January 16, 2018
- Join MünsteR for our next meetup on obtaining functional implications of gene expression data with R - January 24, 2018
- April 12th & 13th in Hamburg: Workshop on Deep Learning with Keras and TensorFlow in R - February 6, 2018
- Another Game of Thrones network analysis - this time with tidygraph and ggraph - March 4, 2018
- Join MünsteR for our next meetup on deep learning with Keras and R - March 28, 2018
- My upcoming meetup talks about Deep Learning with Keras and explaining complex Machine Learning Models with LIME - March 28, 2018
- Meetup slides: Introducing Deep Learning with Keras - April 11, 2018
- HH Data Science Meetup slides: Explaining complex machine learning models with LIME - April 18, 2018
- Look, something shiny: How to use R Shiny to make Münster traffic data accessible. Join MünsteR for our next meetup! - April 19, 2018
- Update: Can we predict flu outcome with Machine Learning in R? - April 22, 2018
- Comparing dependencies of popular machine learning packages with `pkgnet` - April 30, 2018
- July 5th & 6th in Münster: Workshop on Deep Learning with Keras and TensorFlow in R - May 22, 2018
- rOpenSci unconference 2018 + introduction to TensorFlow Probability & the 'greta' package - May 30, 2018
- It's that easy! Image classification with keras in roughly 100 lines of code. - June 15, 2018
- Explaining Keras image classification models with lime - June 21, 2018
- Text-to-speech with R - June 27, 2018
- Addendum: Text-to-Speech with the googleLanguageR package - June 29, 2018
- Code for Workshop: Introduction to Machine Learning with R - June 29, 2018
- Explaining Black-Box Machine Learning Models - Code Part 1: tabular data + caret + iml - July 20, 2018
- Explaining Black-Box Machine Learning Models - Code Part 2: Text classification with LIME - July 26, 2018
- MünsteR Meetup on Blog Mining: Deriving the success of blog posts from metadata and text data. - August 1, 2018
- November 8th & 9th in Munich: Workshop on Deep Learning with Keras and TensorFlow in R - September 19, 2018
- Image clustering with Keras and k-Means - October 6, 2018
- Using R to help plan the future of transport. Join MünsteR for our next meetup! - October 10, 2018
- Trust in ML models. Slides from TWiML & AI EMEA Meetup + iX Articles - December 6, 2018
- Code for case study - Customer Churn with Keras/TensorFlow and H2O - December 12, 2018
- February 21st & 22nd: End-2-End from a Keras/TensorFlow model to production - January 7, 2019
- Don’t reinvent the wheel: making use of shiny extension packages. Join MünsteR for our next meetup! - January 8, 2019
- Lecture slides: Real-World Data Science (Fraud Detection, Customer Churn & Predictive Maintenance) - January 16, 2019
- My course on Hyperparameter Tuning in R is now on Data Camp! - January 17, 2019
- How to prepare data for NLP (text classification) with Keras and TensorFlow - January 23, 2019
- Book review: Beyond Spreadsheets with R - January 31, 2019
- Getting started with RMarkdown & trying to make it in the world of Kaggle. Join MünsteR for our next meetup! - March 6, 2019
- Upcoming talks in spring 2019 - March 22, 2019
- Before you take my DataCamp course please consider this info - April 21, 2019
- Word2Vec Text Mining & Parallelization in R. Join MünsteR for our next meetup! - June 26, 2019
- Baby Weight Shiny app - September 7, 2020
- Update with TF 2.0: Image classification with Keras and TensorFlow - September 13, 2020
- Whose dream is this? When and how to use the Keras Functional API - September 19, 2020
- Video + code from workshop on Deep Learning with Keras and TensorFlow - October 19, 2020
- The Good, the Bad and the Ugly: how (not) to visualize data - October 20, 2020
- k-Means 101: An introductory guide to k-Means clustering in R - March 14, 2021
- Update to Code for case study - Customer Churn with Keras/TensorFlow and H2O - March 18, 2021
- The Good, the Bad and the Ugly: how to visualize Machine Learning data - April 27, 2021
- Data Storytelling code - October 31, 2021
- Data Storytelling presentation - April 26, 2022
- RConsortium interview about MünsteR - November 30, 2022
- What's so great about Explainable AI? - May 24, 2023
meetup (17)
- MICE (Multiple Imputation by Chained Equations) in R - sketchnotes from MünsteR Meetup - November 28, 2017
- Join MünsteR for our next meetup on obtaining functional implications of gene expression data with R - January 24, 2018
- Join MünsteR for our next meetup on deep learning with Keras and R - March 28, 2018
- My upcoming meetup talks about Deep Learning with Keras and explaining complex Machine Learning Models with LIME - March 28, 2018
- Meetup slides: Introducing Deep Learning with Keras - April 11, 2018
- HH Data Science Meetup slides: Explaining complex machine learning models with LIME - April 18, 2018
- Look, something shiny: How to use R Shiny to make Münster traffic data accessible. Join MünsteR for our next meetup! - April 19, 2018
- MünsteR Meetup on Blog Mining: Deriving the success of blog posts from metadata and text data. - August 1, 2018
- I'll be talking at the R-Ladies Meetup about Interpretable Deep Learning with R, Keras and LIME - September 17, 2018
- I'll be talking about 'Decoding The Black Box' at the Frankfurt Data Science Meetup - September 19, 2018
- Slides from talk: 'Decoding The Black Box' at the Frankfurt Data Science Meetup - September 27, 2018
- Using R to help plan the future of transport. Join MünsteR for our next meetup! - October 10, 2018
- Slides from my talk at the R-Ladies Meetup about Interpretable Deep Learning with R, Keras and LIME - October 17, 2018
- TWIMLAI European Online Meetup about Trust in Predictions of ML Models - November 13, 2018
- Don’t reinvent the wheel: making use of shiny extension packages. Join MünsteR for our next meetup! - January 8, 2019
- Getting started with RMarkdown & trying to make it in the world of Kaggle. Join MünsteR for our next meetup! - March 6, 2019
- Word2Vec Text Mining & Parallelization in R. Join MünsteR for our next meetup! - June 26, 2019
sketchnotes (14)
- MICE (Multiple Imputation by Chained Equations) in R - sketchnotes from MünsteR Meetup - November 28, 2017
- Explaining Predictions of Machine Learning Models with LIME - Münster Data Science Meetup - December 12, 2017
- Registration now open for workshop on Deep Learning with Keras and TensorFlow using R - December 20, 2017
- TWiMLAI talk 88 sketchnotes: Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru - January 10, 2018
- Sketchnotes from TWiML&AI #91: Philosophy of Intelligence with Matthew Crosby - January 14, 2018
- Sketchnotes from TWiML&AI #92: Learning State Representations with Yael Niv - January 19, 2018
- Sketchnotes from TWiML&AI #94: Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley - January 28, 2018
- Sketchnotes from TWiML&AI #111: Learning “Common Sense” and Physical Concepts with Roland Memisevic - February 19, 2018
- Sketchnotes from TWiML&AI #115: Scaling Machine Learning at Uber with Mike Del Balso - March 7, 2018
- Sketchnotes from TWiML&AI #124: Systems and Software for Machine Learning at Scale with Jeff Dean - April 18, 2018
- Sketchnotes from TWiML&AI #121: Reproducibility and the Philosophy of Data with Clare Gollnick - April 22, 2018
- Sketchnotes from TWiML&AI: Adversarial Attacks Against Reinforcement Learning Agents with Ian Goodfellow & Sandy Huang - May 14, 2018
- Sketchnotes from TWiML&AI: Practical Deep Learning with Rachel Thomas - June 18, 2018
- Sketchnotes from TWiML&AI: Evaluating Model Explainability Methods with Sara Hooker - October 12, 2018
twimlai (12)
- Explaining Predictions of Machine Learning Models with LIME - Münster Data Science Meetup - December 12, 2017
- TWiMLAI talk 88 sketchnotes: Using Deep Learning and Google Street View to Estimate Demographics with Timnit Gebru - January 10, 2018
- Sketchnotes from TWiML&AI #91: Philosophy of Intelligence with Matthew Crosby - January 14, 2018
- Sketchnotes from TWiML&AI #92: Learning State Representations with Yael Niv - January 19, 2018
- Sketchnotes from TWiML&AI #94: Neuroevolution: Evolving Novel Neural Network Architectures with Kenneth Stanley - January 28, 2018
- Sketchnotes from TWiML&AI #111: Learning “Common Sense” and Physical Concepts with Roland Memisevic - February 19, 2018
- Sketchnotes from TWiML&AI #115: Scaling Machine Learning at Uber with Mike Del Balso - March 7, 2018
- Sketchnotes from TWiML&AI #124: Systems and Software for Machine Learning at Scale with Jeff Dean - April 18, 2018
- Sketchnotes from TWiML&AI #121: Reproducibility and the Philosophy of Data with Clare Gollnick - April 22, 2018
- Sketchnotes from TWiML&AI: Adversarial Attacks Against Reinforcement Learning Agents with Ian Goodfellow & Sandy Huang - May 14, 2018
- Sketchnotes from TWiML&AI: Practical Deep Learning with Rachel Thomas - June 18, 2018
- Sketchnotes from TWiML&AI: Evaluating Model Explainability Methods with Sara Hooker - October 12, 2018
machine-learning (10)
- Data Science for Fraud Detection - September 6, 2017
- Looking beyond accuracy to improve trust in machine learning - January 10, 2018
- I talk about machine learning with Daniel Mies (Podcast in German, though) - February 1, 2018
- Update: Can we predict flu outcome with Machine Learning in R? - April 22, 2018
- Comparing dependencies of popular machine learning packages with `pkgnet` - April 30, 2018
- Code for Workshop: Introduction to Machine Learning with R - June 29, 2018
- Machine Learning Basics - Random Forest - October 30, 2018
- 'How do neural nets learn?' A step by step explanation using the H2O Deep Learning algorithm. - November 6, 2018
- Machine Learning Basics - Gradient Boosting & XGBoost - November 29, 2018
- How do Convolutional Neural Nets (CNNs) learn? + Keras example - January 9, 2019
keras (9)
- My upcoming meetup talks about Deep Learning with Keras and explaining complex Machine Learning Models with LIME - March 28, 2018
- Meetup slides: Introducing Deep Learning with Keras - April 11, 2018
- It's that easy! Image classification with keras in roughly 100 lines of code. - June 15, 2018
- Explaining Keras image classification models with lime - June 21, 2018
- Image clustering with Keras and k-Means - October 6, 2018
- How to prepare data for NLP (text classification) with Keras and TensorFlow - January 23, 2019
- Update with TF 2.0: Image classification with Keras and TensorFlow - September 13, 2020
- Whose dream is this? When and how to use the Keras Functional API - September 19, 2020
- Video + code from workshop on Deep Learning with Keras and TensorFlow - October 19, 2020
münster (9)
- MICE (Multiple Imputation by Chained Equations) in R - sketchnotes from MünsteR Meetup - November 28, 2017
- Join MünsteR for our next meetup on obtaining functional implications of gene expression data with R - January 24, 2018
- Join MünsteR for our next meetup on deep learning with Keras and R - March 28, 2018
- Look, something shiny: How to use R Shiny to make Münster traffic data accessible. Join MünsteR for our next meetup! - April 19, 2018
- MünsteR Meetup on Blog Mining: Deriving the success of blog posts from metadata and text data. - August 1, 2018
- Using R to help plan the future of transport. Join MünsteR for our next meetup! - October 10, 2018
- Don’t reinvent the wheel: making use of shiny extension packages. Join MünsteR for our next meetup! - January 8, 2019
- Getting started with RMarkdown & trying to make it in the world of Kaggle. Join MünsteR for our next meetup! - March 6, 2019
- Word2Vec Text Mining & Parallelization in R. Join MünsteR for our next meetup! - June 26, 2019
conference (5)
- Blockchain & distributed ML - my report from the data2day conference - September 28, 2017
- JAX 2018 talk announcement: Deep Learning - a Primer - January 30, 2018
- Announcing my talk about explainability of machine learning models at Minds Mastering Machines conference - February 1, 2018
- Slides from my JAX 2018 talk: Deep Learning - a Primer - April 27, 2018
- W-JAX 2018 talk: Deep Learning - a Primer - August 29, 2018
workshop (5)
- Workshop on Deep Learning with Keras and TensorFlow in R - November 20, 2017
- April 12th & 13th in Hamburg: Workshop on Deep Learning with Keras and TensorFlow in R - February 6, 2018
- July 5th & 6th in Münster: Workshop on Deep Learning with Keras and TensorFlow in R - May 22, 2018
- November 8th & 9th in Munich: Workshop on Deep Learning with Keras and TensorFlow in R - September 19, 2018
- February 21st & 22nd: End-2-End from a Keras/TensorFlow model to production - January 7, 2019
python (4)
- Explaining Predictions of Machine Learning Models with LIME - Münster Data Science Meetup - December 12, 2017
- Registration now open for workshop on Deep Learning with Keras and TensorFlow using R - December 20, 2017
- Meetup slides: Introducing Deep Learning with Keras - April 11, 2018
- HH Data Science Meetup slides: Explaining complex machine learning models with LIME - April 18, 2018
jax (3)
- JAX 2018 talk announcement: Deep Learning - a Primer - January 30, 2018
- Slides from my JAX 2018 talk: Deep Learning - a Primer - April 27, 2018
- W-JAX 2018 talk: Deep Learning - a Primer - August 29, 2018
webinar (2)
- From Biology to Industry. A Blogger’s Journey to Data Science. - September 20, 2017
- Slides from my SAP webinar: Explaining Keras Image Classification Models with LIME - August 21, 2018
archive (1)
- Find all my other posts on my old website! - July 1, 2017
blogdown (1)
- Moving my blog to blogdown - September 12, 2017
codecentric (1)
- Looking beyond accuracy to improve trust in machine learning - January 10, 2018
codecentric.ai (1)
- Launching codecentric.AI Bootcamp course! - February 8, 2019
data2day (1)
- Blockchain & distributed ML - my report from the data2day conference - September 28, 2017
datacamp (1)
- Before you take my DataCamp course please consider this info - April 21, 2019
github (1)
- Migrating from GitHub to GitLab with RStudio (Tutorial) - September 4, 2017
gitlab (1)
- Migrating from GitHub to GitLab with RStudio (Tutorial) - September 4, 2017
gradient-boosting (1)
- Machine Learning Basics - Gradient Boosting & XGBoost - November 29, 2018
podcast (1)
- I talk about machine learning with Daniel Mies (Podcast in German, though) - February 1, 2018
random-forest (1)
- Machine Learning Basics - Random Forest - October 30, 2018
xgboost (1)
- Machine Learning Basics - Gradient Boosting & XGBoost - November 29, 2018
