Reinforcement learning for Online Ad Serving with Multi Armed Bandits
Deep Dive into the innovative intersection of machine learning and digital advertising, offering insights into how reinforcement learning can revolutionize ad serving strategies.
Prabhakaran SPrincipal Data Scientist
Included in All-Access, one membership for every course.
- Lessons
- 14, in 4 chapters
- Video
- 1 h 40 min
- Certificate
- On completion
What you'll be able to do
- Understand basics of Reinforcement Learning (RL) and ad serving problem statement
- Learn RL strategies to maximize clickthrough rates for ad serving
- Basic to advanced implementations of Multi Armed Bandits
- Explore Reinforcement Learning Algorithms
- Hands on reproducible Python Codes
- No prior knowledge of RL needed
Course content
4 chapters · 14 lessons · 1 h 40 min
01Business and Problem understanding7 lessons · 42 min
- Introduction to online advertising13:25
- Download Resources1:00
- Ad Channels4:02
- Overview of Multi Armed Bandits (MAB)7:21
- Regret (revision)3:37
- Exploitation vs Exploration5:25
- Problem Statement7:32
02Implement Strategies3 lessons · 30 min
- Random selection approach7:49
- Upper Confidence Bound (UCB1) Strategy20:41
- Course Review1:00
03Thompson Sampling3 lessons · 27 min
- Beta Distribution17:26
- Understand and implement7:02
- Greedy and Epsilon Greedy3:00
04Practice and Self Assessment1 lesson · 3 min
- Practice and Self Assessment3:00
What you need
- Basics of Python
- Foundational knowledge of Data Science
- High school maths
Who this course is for
- Data Science Aspirants
- Data Science Professionals
- Software/Data engineers interested in quantitative analysis
- Professionals working with large datasets
- Data analysts, economists, researchers
Your instructor
Prabhakaran S
Principal Data Scientist
My name is Selva, and I am super excited to mentor you on this course!
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 and 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 on-the-job experience. Hope you love it!
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- 4.92
- learners
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- courses
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Questions
How do I get this course?
It is part of All-Access: one membership that opens all 85 courses. The plans and prices are on our course site. You can watch the free preview lessons before you join.
Can I get a refund?
Yes. If the membership is not right for you, ask for a refund within 30 days of your first payment.
Can I learn on my phone?
Yes. Lessons play in the browser on any phone, tablet or computer, and your place is saved for the next device.
I am already a member. Where are my courses?
On our course site, edu.machinelearningplus.com. Sign in there with the email you joined with. The courses move to this site later, with your access, and you will not pay again.
