Understanding Stan
Stan is a powerful statistical modeling language that excels in Bayesian inference, utilizing efficient C libraries for computational performance. The discussion highlights the importance of gradients in model training, drawing parallels to popular libraries like TensorFlow and PyTorch, which facilitate differentiation and optimization of model weights. Understanding these concepts is crucial for effectively leveraging statistical models in data science.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 507: Bayesian Statistics — with Rob Trangucci
Related Questions