Mining Data from Variable Dependencies
This course will teach you several models like Bayesian Networks, LBP, Variable Elimination, etc. with the help of which you can derive complex relationships across multiple input variables or features.
What you'll learn
Mining data involves deriving complex probabilistic relationships between multiple variables. In this course, Mining Data from Variable Dependencies, you’ll learn to apply probabilistic graph models to derive complex relationships across variables/features. First, you’ll explore Bayesian Networks. Next, you’ll discover D Separation. Finally, you’ll learn how to perform data fragmentation. When you’re finished with this course, you’ll have the skills and knowledge of Python Probabilistic models needed to explore relationships across variables/input features to derive joint probabilities, or impact of features on the final outcome.
Table of contents
- Introduction to Structure Learning 2m
- Constraint Based Learning: Part One 2m
- Constraint Based Learning: Part Two 1m
- Constraint Based Learning: Part Three 1m
- Demo: Constraint Based Approach 4m
- Score Based Learning: Part One 3m
- Score Based Learning: Part Two 2m
- Score Based Learning: Part Three 1m
- Demo: Score Based Approach 6m
- Summary 1m
- Introduction to Parameter Learning 1m
- The Likelihood Function 2m
- Demo: MLE for Parameter Estimation 3m
- MLE for Bayesian Networks 1m
- Demo: Bayesian Parameter Learning for Job Interview Case Study 2m
- Demo: Bayesian for Parameter Estimation 9m
- Data Fragmentation 1m
- Demo: Data Fragmentation 3m
- Bayes Parameter Estimation 1m
- Demo: Bayesian Estimation for the Bayesian Network 8m
- Summary 0m
About the author
Niraj is a AWS/Azure DevSecOps Cloud Specialist with over a decade of work experience into Data Modeling with Databases like Cassandra, MongoDB, SparkSQL, ElasticSearch and SQL Server. He has over 7 years of work ex into Computer Vision, Artificial Intelligence, DevOps, Machine Learning and Big Data Stack, he has been a consultant to companies like CISCO, ERICSSON, Dynamic Elements and JP Morgan He has excellent data visualization/ analytics skills and quite proficient in languages like Python ,... more