Introduction to PyMC3 for Bayesian Modeling and Inference

About this Course

The objective of this course is to introduce PyMC3 for Bayesian Modeling and Inference, The attendees will start off by learning the the basics of PyMC3 and learn how to perform scalable inference for a variety of problems. This will be the final course in a specialization of three courses .Python and Jupyter notebooks will be used throughout this course to illustrate and perform Bayesian modeling with PyMC3.. The course website is located at The course notebooks can be downloaded from this website by following the instructions on page The instructor for this course will be Dr. Srijith Rajamohan.

Created by: Databricks


Related Online Courses

The ultimate goal of a computer vision system is to generate a detailed symbolic description of each image shown. This course focuses on the all-important problem of perception. We first describe... more
Health systems worldwide seek to prevent and treat disease and illness and improve well-being and quality of life. This specialisation focuses on improving the quality of the services provided by... more
This Specialization provides a full course in Digital Signal Processing, with a focus on audio processing and data transmission. You will start from the basic concepts of discrete-time signals and... more
Forms are an essential part of modern-day workflow. They are the primary medium of collecting, validating, and storing user data to provide great user experience. React library helps in developing... more
The University of California San Diego, Skaggs School of Pharmacy and Pharmaceutical Sciences Drug Discovery course brings you lectures from both faculty and industry experts. With this course,... more

CONTINUE SEARCH

FOLLOW COLLEGE PARENT CENTRAL