Python-bloggers

At Appsilon, we’ve been integrating Large Language Models into Shiny for Python applications for a while now. One thing became clear: the challenge isn’t in the initial integration. Shiny for Python’s ui.Chat component makes that straightforward. The real complexity lies in building applications that can evolve ...

In the past, many organizations relied on static file reports to make decisions. Typically, several Excel and PowerPoint reports are generated each month. Management would gather, discuss results, decide, and move to email other systems or meet with their teams to pass these decisions forward. There are multiple problems with ...

The directional relationship between asset returns can make or break investment decisions. Investors and analysts make use of a covariance calculator to measure how two assets move together. Positive values show similar directional movement while negative values point to opposite movements. Statistical data reveals that two stocks ABC and XYZ ...

Customizing the {riskassessment} App based on your organization’s needs makes validating R packages in regulated industries like pharma more efficient and compliant. Strict compliance rules and best practices mean organizations need a reliable way to assess and approve packages. The {riskassessment} App, built on {riskmetric}, provides a structured, user-friendly ...

The electronic manufacturing and supply chain industry is complex and competitive, and in order to thrive, companies need an innovative approach to managing CPQ (configure, price, quote). Since customer experience is a key driver for profitability, you need a CPQ tool built for supply chain management in the electronics industry ...

Call for abstracts now open We are excited to announce the Call for Abstracts for Shiny in Production 2025, to be held on 8th-9th October 2025 in Newcastle upon Tyne, UK. This event brings together industry experts, data scientists, and developer...

Demo usage of tisthemachinelearner, in Python and R