Bayesian

Sort options

Probabilistic Graphical Models 3: Learning (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine [...]
10
Average: 10 ( 3 votes )

Probabilistic Graphical Models 1: Representation (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine [...]
0
No votes yet

Game Theory (Coursera)

Popularized by movies such as "A Beautiful Mind," game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Beyond what we call `games' in common language, such as chess, poker, soccer, etc., it includes the modeling of conflict among nations, political campaigns, competition among firms, [...]
4
Average: 4 ( 3 votes )

Bayesian Statistics (Coursera)

This course describes Bayesian statistics, in which one's inferences about parameters or hypotheses are updated as evidence accumulates. You will learn to use Bayes’ rule to transform prior probabilities into posterior probabilities, and be introduced to the underlying theory and perspective of the Bayesian paradigm. [...]
0
No votes yet

Robotics: Estimation and Learning (Coursera)

How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered [...]
10
Average: 10 ( 4 votes )

Bayesian Statistics: From Concept to Data Analysis (Coursera)

This course introduces the Bayesian approach to statistics, starting with the concept of probability and moving to the analysis of data. We will learn about the philosophy of the Bayesian approach as well as how to implement it for common types of data. We will compare the Bayesian approach [...]
4
Average: 4 ( 3 votes )

Data Science Math Skills (Coursera)

Sep 13th 2021
Data Science Math Skills (Coursera)
Course Auditing
Categories
Effort
Languages
Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra [...]
5
Average: 5 ( 3 votes )

Improving your statistical inferences (Coursera)

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how [...]
6
Average: 6 ( 4 votes )

Bayesian probability theory (iMooX)

The primary motivation for this course is to warm a broader audience to probability theory, as it is central to all scientific fields. Or as E.T. Jaynes - one of the most important researchers on probability theory of the last century - put it: "Probability is the logic of science." [...]
0
No votes yet