Causal Data Science

Causal Data Science

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Causal Discovery

Learn the core concepts of machine learning, causal discovery, and data visualization through clear, hands-on Python examples. Master both theory and practice to apply these techniques confidently in real-world scenarios!
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19:55
Mastering Causal Thinking: How to Build Causal Strategies For Real-World Environments.
19:55
Mastering Causal Thinking: How to Build Causal Strategies For Real-World Environments.
The journey from raw data to actionable results goes through four progressive stages of analytics: Descriptive, Diagnostic, Predictive, and…
 • erdogant
11:13
What Are PCA Loadings And How To Effectively Use Biplots?
A practical guide for getting the most out of Principal Component Analysis.
 • erdogant
13:53
The Complete Starters Guide For Causal Discovery using Bayesian Modeling.
This Blog and Podcast is an extensive starter guide where I will walk you through causal discovery approaches with its applications, libraries, and…
 • erdogant
20:22
How to Find the Best Theoretical Distribution for Your Data
Knowing the underlying data distribution is an essential step for data modeling and has many applications, such as anomaly detection, synthetic data…
 • erdogant
6:57
Detection of Statistical Significant Associations in Mixed Data sets.
Detecting the connectivity is an important but challenging step. I will demonstrate how to detect variables with similar behavior in tabular/mixed data…
 • erdogant
9:43
D3Blocks: The Python Library to Create Interactive and Standalone D3js Charts.
Create interactive, stand-alone, and visually attractive charts that are built on the graphics of d3 javascript (d3js) but configurable with Python. The…
 • erdogant
12:27
Chat with Your Dataset using Bayesian Inferences.
The ability to ask questions to your data set has always been an intriguing prospect. You will be surprised how easy it is to learn a local Bayesian…
 • erdogant
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