Bayesian Statistics Supervised Learning AB Testing

Bayesian Statistics & Supervised Learning – A/B Testing, available at $19.99, has an average rating of 4.45, with 8 lectures, based on 15 reviews, and has 5197 subscribers.

You will learn about Apply Bayesian methods to A/B testing and also use adaptive algorithms to improve A/B testing performance Naive Bayes Classifier introduction and Use of naive bayes in Machine Learning Understanding A/B testing and Split tests Power of A/B and testing and Example solving in Python using dummy data This course is ideal for individuals who are Anyone who wants to learn about data and analytics or Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers It is particularly useful for Anyone who wants to learn about data and analytics or Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers.

Enroll now: Bayesian Statistics & Supervised Learning – A/B Testing

Summary

Title: Bayesian Statistics & Supervised Learning – A/B Testing

Price: $19.99

Average Rating: 4.45

Number of Lectures: 8

Number of Published Lectures: 8

Number of Curriculum Items: 8

Number of Published Curriculum Objects: 8

Original Price: $89.99

Quality Status: approved

Status: Live

What You Will Learn

Apply Bayesian methods to A/B testing and also use adaptive algorithms to improve A/B testing performance

Naive Bayes Classifier introduction and Use of naive bayes in Machine Learning

Understanding A/B testing and Split tests

Power of A/B and testing and Example solving in Python using dummy data

Who Should Attend

Anyone who wants to learn about data and analytics

Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers

Target Audiences

Anyone who wants to learn about data and analytics

Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers

Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data. Such algorithms operate by building a model from example inputs and using that to make predictions or decisions, rather than following strictly static program instructions. Machine learning is closely related to and often overlaps with computational statistics; a discipline that also specializes in prediction-making.

Through this training we are going to apply Bayesian methods to A/B testing and also use adaptive algorithms to improve A/B testing performance.

The training will include the following;

– Naive Bayes Classifier introduction
– Use of naive bayes in Machine Learning
– Understanding A/B testing
– Split tests
– Power of A/B and testing
– Example solving in Python using dummy data

Bayesian statistics is a particular approach to applying probability to statistical problems. It provides us with mathematical tools to update our beliefs about random events in light of seeing new data or evidence about those events. Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. In particular Bayesian inference interprets probability as a measure of believability or confidence that an individual may possess about the occurance of a particular event.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Bayesian Machine Learning

Chapter 2: Code

Lecture 1: Example of Bayesian Machine Learning

Lecture 2: Example of Bayesian Machine Learning Continues

Lecture 3: MCMC Module of PYMC Implementation

Lecture 4: Running the MCMC Module

Chapter 3: Multiple Variant Testing

Lecture 1: Multiple Variant Testing Using Hierarchial Model

Lecture 2: Example of Multiple Variant Testing

Lecture 3: Example of Multiple Variant Testing Continues

Instructors

EDUCBA Bridging the Gap
Learn real world skills online

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1 stars: 1 votes

2 stars: 0 votes

3 stars: 2 votes

4 stars: 1 votes

5 stars: 11 votes

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