Saltar al contenido principal
InicioPythonBayesian Data Analysis in Python

Bayesian Data Analysis in Python

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Comience El Curso Gratis
4 Horas14 Videos49 Ejercicios
11.003 AprendicesDeclaración de cumplimiento

Crea Tu Cuenta Gratuita

o

Al continuar, acepta nuestros Términos de uso, nuestra Política de privacidad y que sus datos se almacenan en los EE. UU.
¿Entrenar a 2 o más personas?Pruebe DataCamp para empresas

Descripción del curso

Bayesian data analysis is an increasingly popular method of statistical inference, used to determine conditional probability without having to rely on fixed constants such as confidence levels or p-values. In this course, you’ll learn how Bayesian data analysis works, how it differs from the classical approach, and why it’s an indispensable part of your data science toolbox. You’ll get to grips with A/B testing, decision analysis, and linear regression modeling using a Bayesian approach as you analyze real-world advertising, sales, and bike rental data. Finally, you’ll get hands-on with the PyMC3 library, which will make it easier for you to design, fit, and interpret Bayesian models.
Empresas

.css-1goj2uy{margin-right:8px;}Group.css-gnv7tt{font-size:20px;font-weight:700;white-space:nowrap;}.css-12nwtlk{box-sizing:border-box;margin:0;min-width:0;color:#05192D;font-size:16px;line-height:1.5;font-size:20px;font-weight:700;white-space:nowrap;}¿Entrenar a 2 o más personas?

Obtenga acceso de su equipo a la biblioteca completa de DataCamp, con informes centralizados, tareas, proyectos y más
Pruebe DataCamp Para EmpresasPara obtener una solución a medida, reserve una demostración.

Ir a la pista
1. 1

The Bayesian way

Gratuito

Take your first steps in the Bayesian world. In this chapter, you’ll be introduced to the basic concepts of probability and statistical distributions, as well as to the famous Bayes' Theorem, the cornerstone of Bayesian methods. Finally, you’ll build your first Bayesian model to draw conclusions from randomized coin tosses.

Reproducir Capítulo Ahora
Who is Bayes? What is Bayes?
50 xp
Bayesians vs. Frequentists
100 xp
Probability distributions
100 xp
Probability and Bayes' Theorem
50 xp
Let's play cards
100 xp
Bayesian spam filter
100 xp
What does the test say?
50 xp
Tasting the Bayes
50 xp
Tossing a coin
100 xp
The more you toss, the more you learn
100 xp
Hey, is this coin fair?
100 xp
2. 2

Bayesian estimation

It’s time to look under the Bayesian hood. You’ll learn how to apply Bayes' Theorem to drug-effectiveness data to estimate the parameters of probability distributions using the grid approximation technique, and update these estimates as new data become available. Next, you’ll learn how to incorporate prior knowledge into the model before finally practicing the important skill of reporting results to a non-technical audience.

3. 3

Bayesian inference

Apply your newly acquired Bayesian data analysis skills to solve real-world business challenges. You’ll work with online sales marketing data to conduct A/B tests, decision analysis, and forecasting with linear regression models.

4. 4

Bayesian linear regression with pyMC3

In this final chapter, you’ll take advantage of the powerful PyMC3 package to easily fit Bayesian regression models, conduct sanity checks on a model's convergence, select between competing models, and generate predictions for new data. To wrap up, you’ll apply what you’ve learned to find the optimal price for avocados in a Bayesian data analysis case study. Good luck!

Empresas

Group¿Entrenar a 2 o más personas?

Obtenga acceso de su equipo a la biblioteca completa de DataCamp, con informes centralizados, tareas, proyectos y más

En las siguientes pistas

Ir a la pista

Sets De Datos

Michał Oleszak

Machine Learning Engineer

Ver Mas

Crea Tu Cuenta Gratuita

o

Al continuar, acepta nuestros Términos de uso, nuestra Política de privacidad y que sus datos se almacenan en los EE. UU.