Scaling Shiny apps requires load balancing with session affinity which is not a trivial matter. Read on to see how to do that on Heroku.

A Forecasting API, with examples

This post shows how filling histograms can be done in very different ways thereby connecting very different areas: from gradient boosted trees to SQL queries to one-hot encoding. Let's jump into it! Modern gradient boosted trees (GBT) like LightGBM, XGBoost and the HistGradientBoostingRegressor of scikit-learn all use two techniques on ...

Lasso regression is another algorithm that uses regularization to handle variables. Essentially, this algorithm will reduce coefficients to zero based on whether they contribute meaningfully to the results. The video below will explain how to use Lasso regression in Python.

Want to automate Whatsapp messages? Try PyWhatKit - A Python Whatsapp automation library.

We’re happy to announce a new data science in Python course by Appsilon has been released and is available to everyone for free, as open-source material! Check out the course repository on GitHub!  The course is a great way to introduce yourself to the Data Science world. It does ...

There’s one major problem with ChromeDriver: anti-bot services are able to detect that a browser session is being automated (as opposed to being used by a regular meat sack) and will often impose restrictions or deny connections altogether. The Undetected ChromeDriver (undetected-chromedriver) Python package is a patched version of ...

Ridge regression belongs to a family of regression called regularization regression. This family of regression uses various mathematical techniques to reduce or remove coefficients from a regression model. In the case of ridge, this algorithm will reduce coefficients close to zero but never actually remove variables from a model. In ...

Here at Jumping Rivers we like to keep our courses up to date so we can bring you training on the latests tools and technologies. To this end, we have recently added two new courses to our listing...