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Causal Inference for Data Science | Manning Publications

May 16, 2024

Causal Inference for Data Science | Manning Publications
English | eBook | Size: 8.52 MB

When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.

Linkedin Learning – Causal Inference With Survey Data

May 13, 2024

Linkedin Learning – Causal Inference With Survey Data
English | Tutorial | Size: 295.50 MB

Is y really equal to 0.5x? Is education really good for you? Is taxation policy really changing spending behavior? To answer such questions, you often need to infer causality from survey data. To do that, you need to understand the empirical tools available to data analysts.

Linkedin Learning – Machine Learning and AI Foundations: Causal Inference and Modeling

August 6, 2022

Linkedin Learning – Machine Learning and AI Foundations Causal Inference and Modeling-XQZT
English | Tutorial | Size: 469.51 MB

Learn about the modeling techniques and experimental designs that allow you to establish causal inference, and how to use them

ODSC West 2020 Probabilistic Programming and Bayesian Inference with Python

December 14, 2020

ODSC West 2020 Probabilistic Programming and Bayesian Inference with Python
English | Size: 1.51 GB
Category: Tutorial

If you can write a model in sklearn, you can make the leap to Bayesian inference with PyMC3, a user-friendly intro to probabilistic programming (PP) in Python. PP just means building models where the building blocks are probability distributions! And we can use PP to do Bayesian inference easily. Bayesian inference allows us to solve problems that aren’t otherwise tractable with classical methods.