Have a look at what my team and I worked on during the Permafrost Hackathon in Zurich. The goal was to detect movements from multitemporal images. Since the images didn’t have any labels, we used unsupervised learning methods. Check it out, yo!
This blog is a hands-on experience in Dash, presenting core components, how to display figures with callbacks, supplying you with a working web application to play with, and the resources to build your own. Dash is a powerful tool for Python developers. Developed by the team behind Plotly, Dash is an open-source framework built on top of Flask, Plotly.js, and React.js.
Newman and Postman form a great team to test your REST API. I will give you a quick roundtrip through both tools and their interplay: define requests and tests, export them, and let them run with CLI and within Jenkins.
A new field of Machine Learning is born: Causal Machine Learning. Learn here about the Causal Forest, one of the most famous Causal Machine Learning algorithms for estimating heterogeneous treatment effects.
A new field of Machine Learning is born: Causal Machine Learning. Learn here what it is and why it is crucial for the future of Data Science.
A few weeks ago, several of our colleagues here at STATWORX participated in an exciting time series competition, hosted by a large german-based company.
This was the opportunity for us to organize an internal hackathon in our office in Frankfurt. In this blog article, Marlon will give you an insight into how we plan and execute such hackathons at STATWORX.
Beim Erarbeiten neuer Skills und Tools ist der Einstieg nicht immer einfach. In der STATWORX Academy bieten wir daher eine Fülle an Schulungsformaten an, in denen wir Dir den Einsteig in den Bereich Data Science erleichtern wollen. Unser Kollege Jan erzählt in diesem Blogartikel vom “R for Data Science” Workshop, den er in unserem Frankfurter Office geleitet hat. Erfahre in diesem Artikel, an wen sich der Kurs richtet und welche Inhalte geboten werden.
Once again, an amazing year at STATWORX is coming to an end. The frequency and magnitude of positive things happening to our company are continuously increasing with every new client, employee, or partner coming to our company. That is why the very first paragraph of this post ends with a massive THANK YOU to my whole team, our customers and …
Training random forests on time series is one thing, but tuning them? It’s not like you can just apply cross validation and be done with it. Or can you? This post forms part two our mini-series “Time Series Forecasting with Random Forest”. Find out how you can tune the hyperparameters of the random forest algorithm when dealing with time series data. The answers might surprise you!
How can you adjust your prices to meet your sales quota better? By combining sales forecasts and price elasticity estimations, you can make recommendations to increase the profit. In this blog post, Marlon will show you how to combine both methods.