Deep Dive into Bayesian Modeling
Bayesian probability is a powerful technique that has revolutionized many industries by dealing with probability distributions in a different way. Discover techniques such as Markov chain Monte Carlo and Variational Inference, and how to solve multi-armed bandits. This 2-day training offers a deep-dive into this and much more!
What you'll learn
You will learn:
- The theorem that underlies Bayesian data analysis and learn to apply it to solve probabilistic problems.
- How Bayes’ Theorem can be applied to data and make yourself comfortable with the Bayesian terminology: prior distributions, likelihoods, and posterior distributions.
- How The Bayesian paradigm is fundamentally different than the (more famous) “frequentist” paradigm.
- The (practical) pros and cons of working with either the Bayesian or the frequentist approach.
- Markov chain Monte Carlo (MCMC) methods
- How Variational inference offers an alternative to MCMC that is suitable to (very) big data.
Bayesian Probability – Program
The program of this two-day Bayesian Probability training is as follows:
Day 1: Theory and Hands-On Labs
- Fundamentals: Bayes’ Theory
- From Bayes’ Theorem to Bayesian Data Analysis
- The Bayesian’ Paradigm
- Markov chain Monte Carlo with PyMC3
- Variational Inference: Big Data Bayesian Data Analysis
Day 2: Hackathon: Multi-Armed Bandits with the Bayesian approach
Multi-armed bandit problems (like for example A/B testing) can be solved by using Bayesian modeling. Participants will be presented with the simulation environment for Multi-armed bandits and encouraged to code a Bayesian decision-making algorithm. A perfect opportunity to creatively brainstorm and learn more about practical applications of Bayesian theory and effectively balancing the exploration-exploitation tradeoff
Climbing a steep Python and Machine Learning curve in three days. This would have taken me months on my own.
This Bayesian Modeling training is perfect for
- Data Scientists who know Machine Learning and want to learn about Bayesian statistics.
- This training is especially suited for Data Scientists who want to go beyond the standard probability theory.
- To get the most out of this training, we advise that you have at least one year of working experience with Python.
What will you learn during the Bayesian Modeling training:
- You will understand what makes Bayesian Probability so powerful, especially compared to the traditional frequentist approach.
- You will learn how to use the PyMC for building Bayesian models.
- We will also teach you how to apply Markov Chain Monte Carlo, Variational inference and other applications of Bayesian modeling in practice.
Data Science Skills
The Data Science Learney Journey
The training courses in this journey teach you new skills and empower you to stay ahead professionally. We offer solid fundamentals that apply to practical Python courses, whether you are a beginner or an advanced user. We also offer courses on Spark, R, and Deep Learning.
The Right Format For Your Preferred Learning Style
At GoDataDriven we offer four distinct training modalities:
- In-Classroom & In-Company Training
- Online, Instructor-Led Training
- Hybrid and Blended Learning
- Self-Paced Training