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The helfRlein package – A collection of useful functions

Unfold 2022 in Bern – by Cleverclip

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How to Create Datasets With GitHub Actions

How to Reduce the AI Carbon Footprint as a Data Scientist

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5 Highlights from the Digital Festival Zurich 2021

How to Automatically Create Project Graphs With Call Graph

STATWORX Cheatsheets – Python Basics Cheatsheet for Data Science

Deploy and Scale Machine Learning Models with Kubernetes

3 Scenarios for Deploying Machine Learning Workflows Using MLflow

Car Model Classification III: Explainability of Deep Learning Models With Grad-CAM

Car Model Classification II: Deploying TensorFlow Models in Docker Using TensorFlow Serving

Car Model Classification I: Transfer Learning mit ResNet

2020 – A Year in Review for Me and GPT-3

5 Practical Examples of NLP Use Cases

New Trends in Natural Language Processing – How NLP Becomes Suitable for the Mass-Market

5 Technologies That Every Data Engineer Should Know

Generative Adversarial Networks: How Data Can Be Generated With Neural Networks

Fine-tuning Tesseract OCR for German Invoices

STATWORX 2.0 – Opening of the New Headquarters in Frankfurt

Why You Should Use Containerized Microservices When Deploying Your Data Science Application

How to Build a Machine Learning API with Python and Flask

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Model Regularization – The Bayesian Way

Off To New Adventures: STATWORX Office Soft Opening

Two Patterns To Secure REST APIs

A Social Network Simulation In The Tidyverse

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What’s Your Problem – Framing Data Science Questions The Right Way

Movie Recommendation With Recommenderlab

Airflow for Data Scientists

Making Of: A Free API For COVID-19 Data

How To Build A Dashboard In Python – Plotly Dash Step-by-Step Tutorial

Why Is It Called That Way?! – Origin and Meaning of R Package Names

Defining Your Own Shortcut in RStudio

Community Detection with Louvain and Infomap

Testing REST APIs With Newman

Dynamic UI Elements in Shiny – Part 2

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Machine Learning Goes Causal II: Meet the Random Forest’s Causal Brother

Machine Learning Goes Causal I: Why Causality Matters

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STATWORX 2019 – A Year in Review

Tuning Random Forest on Time Series Data

Combining Price Elasticities and Sales Forecastings for Sales Improvement

Access your Spark Cluster from Everywhere with Apache Livy

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Evaluating Model Performance by Building Cross-Validation from Scratch

Time Series Forecasting With Random Forest

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Dynamic UI Elements in Shiny – Part 1

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Web Scraping 101 in Python with Requests & BeautifulSoup

Getting Started With Flexdashboards in R

Bang Bang – How to program with dplyr

Revisited: Forecasting Last Christmas Search Volume

Simulating the Bias-Variance Tradeoff in R

STATWORX Summer Barbecue 2019

Interactive Network Visualization with R

Coding Random Forests in 100 lines of code*

Using Reinforcement Learning to play Super Mario Bros on NES using TensorFlow

6 Myths About Refueling – Tackled With Statistics

Automated Creation of Docker Containers

How to Speed Up Gradient Boosting by a Factor of Two

R and Python: Using Reticulate to Get the Best of Both Worlds

Fixing the Most Common Problem With Plotly Histograms

Running your R script in Docker

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Plotly – An Interactive Charting Library

Ensemble Methods in Machine Learning: Bagging & Subagging

STATWORX on Tour: Year-End Event in Belgium

Dreaming of a White Christmas – With ggmap in R

Building a Scaleable Deep Learning Serving Environment for Keras Models Using NVIDIA TensorRT Server and Google Cloud

Coding Regression trees in 150 lines of R code

Coding Gradient Boosted Machines in 100 Lines of R Code

Master R shiny: One trick to build maintainable and scaleable event chains

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Forecasting Last Christmas Search Volume on Google Trends Using Deep Learning

Food for Regression: Mixing in Cross-Elasticities and Promotional Effects

A Performance Benchmark of Different AutoML Frameworks

Learning Images with Keras

Custom Themes in ggplot2

CodeR: an LSTM that writes R Code

A Performance Benchmark of Google AutoML Vision Using Fashion-MNIST

Using Themes in ggplot2

Using Machine Learning for Causal Inference

Food for Regression: Using Sales Data to Identify Price Elasticity

A Framework to Automate Your Work: Why Airflow?

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