Dynamic pricing using Multi Armed
Bandit (Reinforcement Learning)

Created by Selva Prabhakaran

10 Video Lessons
English
English captions

Get Subscription

Already Subscribed? Click here to access your courses

Course Certificate
Codes
Practice Data
Clean English Captions
Expert Query Support
Programming Notebooks
Self-paced online videos
15-Day Moneyback Guarantee
Learning duration ~ 2-3 weeks
Complete access for 1 year

What you will learn

Understanding the Basics of Dynamic Pricing.

Introduction to Multi-Armed Bandit Problems.

Understand fundamentals of Reinforcement learning.

Explore MAP algorithms: UCB, Thompson Sampling, Epsilon Greedy.

Application of MAB in Dynamic Pricing.

Hands-on Python with fully worked out project code.

Course Curriculum

Requirements

Basics of Python
Foundational knowledge of Data Science
High school maths

Who should attend this course?

Data Science Aspirants
Data Science Professionals
Software/Data engineers interested in quantitative analysis
Professionals working with large datasets
Data analysts, economists, researchers

Instructor

Selva Prabhakaran Principal Data Scientist

My name is Selva, and I am super excited to mentor you on this project!

I head the Data Science team for a global Fortune 500 company and over the last 10 years of my data science experience I’ve deployed 20+ global products. I’m also the Founder & Chief Author of Machine Learning Plus, which has over 4M annual readers.

I specialize in covering the in-depth intuition and maths of any concept or algorithm. And based on my existing student requests, I’ve put up the series of courses and projects with detailed explanations – just like an on the job experience. Hope you love it!

4.5+Instructor rating
200+ reviews
75K+students
50+ Courses

Sign Up Complete your profile

Log In

You may also be interested in

Dynamic pricing using Multi Armed Bandit (Reinforcement Learning)