{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/8ec110a1f7754a11b31f3a751489eff5\" frameborder=\"0\" width=\"1728\" height=\"1296\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1296,"width":1728,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1296,"thumbnail_width":1728,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/8ec110a1f7754a11b31f3a751489eff5-86a832e539bdbbe9.gif","duration":757.54,"title":"Unlocking Generic Curve Fitting in Synthace Data Preparation 📊","description":"In this tutorial, I introduced some exciting new functionality in the Data Preparation app as part of the Datapack, specifically focusing on generic curve fitting. I demonstrated how to define a custom formula for fitting curves to datasets, using the Michaelis-Menten kinetic curve as an example. I emphasized the importance of setting parameter bounds to enhance fitting accuracy and speed. I also walked through the interface, showing how to input equations and calculate fits. I encourage you to explore these features and apply them in your data analysis for more insightful results."}