Your Guide to Quality Data Science Products

The city of Poznań wanted to know why it didn't rate highly with tourists. So they gave loads of data to a gathering of developers to gain some insight. TL;DR: we learned a lot from the hackathon & won the thing. R Shiny gave us a slight edge. :)

The algorithms we build affect lives. We have an ethical obligation not to teach our machines to be prejudiced. Here are some lessons and examples that will help you achieve this in your machine learning model assembly and use.

We need to build a culture where AI is built with a focus on the entire outcome, not just metrics or profit.

We live in a competitive time, filled with regional and global challenges, both physical and digital, and yet we are empowered with access to ever-growing data sets and tools at our fingertips: cyber-security, NewSpace, asymmetry of information

A recap of satRday Cardiff 2019. New R packages, rstats, education, a hackathon for inclusivity, community, fantasy football, live coding and pizza.

Climate change will exacerbate the consequences of natural disasters. Developing countries will be hit the hardest. We helped Dr. Junko Mochizuki build a decision support tool for policymakers in Madagascar to better mitigate this risk.

Explore ways NGOs can use AI for species conservation or find out how AI pros and data scientists can contribute to real-world projects.

How to help an organization turn piles of paper into a data lake - Now easier with Optical Character Recognition (OCR).

I had the honor to meet people who preserve biodiversity and genetic resources at the GenRes Bridge conference in Tuusula, Finland. I represented Appsilon Data Science's Data for Good initiative and shared pathways for incorporating DS and AI.

To achieve IA implementation success, plan for a partnership between humans and machines, not replacement. Buy-in is crucial, of course. So educate your workforce about IA and plan for hero moments. Automate tasks, not jobs and start small.

What are the differences between AI and IA? When is Intelligence Augmentation superior to a pure Artificial Intelligence approach? Which solution makes the most sense for your problem set? Consider IA solutions when a limited amount of data exists

Describes the best practices for setting automated test architecture for R Shiny apps. Automate and test early and often with unit tests, user interface tests, and performance tests.