Testimonials

• "At Quantopian we use PyMC3 to track uncertainty in the performance of a trading algorithm." - Thomas Wiecki
• "We use PyMC3 to evaluate A/B test performance. Works great with very little code!" - Thomas Hunger, We Are Wizards
• "PyMC3 is used at VoiceBox Technologies to compare algorithm performances using Kruschke's BEST algorithm. More is in development."
• "Used in research code at Channel 4 for developing internal forecasting tools." - Peader Coyle
• "At Managed by Q, we use PyMC3 for all of our statistical modeling, including A/B test analysis, sales forecasting, and churn prediction." - Daniel Weitzenfeld
• "PyMC3 is my primary tool for statistical modeling at Salesforce. I use it to combine disparate sources of information and pretty much anywhere that quantifying uncertainty is important. For example, we build hierarchical models to evaluate varying effects in web experiments and then to build meta-analyses that quantify the expected returns of a subsequent experiment. We've also been experimenting with gaussian processes to model time series data for forecasting." - Eddie Landesberg. Manager, Data Scientist