Adopting Data-Centric Machine Learning For Small Datasets (Guest: Jonas Christensen)

In this episode, Jonas Christensen (Senior Data & Analytics Leader) and Andreas Welsch discuss adopting a data-centric Machine Learning approach for small datasets. Jonas shares learnings on improving data quality before building models and provides valuable advice for listeners looking to improve their results with small data sets.Key topics:- Describe the common challenges businesses still run into with Machine Learning- Evaluate options for working with small data sets- Advise data scientists to get more data and better data- Deliver business value from Machine Learning at a time when everybody wants to chase Generative AIListen to the full episode to hear how you can:- Work toward better data quality over improving your model parameters- Approach data science as a team sport that requires actively influencing your business stakeholders- Share with your stakeholders how you use the data downstream to get them excited about their contributionWatch this episode on YouTube:https://youtu.be/C_GlTgRmeL8Questions or suggestions? Send me a Text Message. Support the show***********Disclaimer: Views are the participants’ own and do not represent those of any participant’s past, present, or future employers. Participation in this event is independent of any potential business relationship (past, present, or future) between the participants or between their employers.Level up your AI Leadership game with the AI Leadership Handbook (https://www.aileadershiphandbook.com) and shape the next generation of AI-ready teams with The HUMAN Agentic AI Edge (https://www.humanagenticaiedge.com).More details: https://www.intelligence-briefing.com All episodes:https://www.intelligence-briefing.com/podcastGet a weekly thought-provoking post in your inbox:https://www.intelligence-briefing.com/newsletter