Data Drifts, Shifts, and Other Phenomena that Degrade Your AI Solution Performance
Data drifts and shifts can harass your ML model’s performance. Learn how to recognize, detect, and tackle them effectively
7 common AI risks you face when you do a machine learning project
Working on machine learning is about doing experiments that usually fail and hard working on data, architecture, and hyperparameters to get satisfying results. However, the road to a working solution is full of pitfalls. Therefore, I have collected for you seven AI risks to monitor when working on an AI solution.
5 quick tips on what to remember when working on your AI solution
Do you want to create an AI solution, but don’t know how to start?
Starting AI research might be tricky, and you should avoid many pitfalls in the initial development phase.
I have prepared a short list of 5 tips to help you start working with machine learning and guide you through the research process.
Adopting AI in your organisation — Custom Solution vs Off-the-shelf Product
Custom solution or off-the-shelf product? What to choose and when if you want to adopt AI in your organisation? It is the dilemma more, and more companies are facing. So let’s see what to consider when making a choice.
