Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications
Ever wondered how AI technologies like OpenAI ChatGPT and GPT-4 really work? In this course, you will learn the foundations of these groundbreaking applications.
When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning.
These tasks are pretty trivial compared to what we think of AIs doing - playing chess and Go, driving cars, and beating video games at a superhuman level.
Reinforcement learning has recently become popular for doing all of that and more.
Much like deep learning, a lot of the theory was discovered in the 70s and 80s but it hasn’t been until recently that we’ve been able to observe first hand the amazing results that are possible.
In 2016 we saw Google’s AlphaGo beat the world Champion in Go.
We saw AIs playing video games like Doom and Super Mario.
Self-driving cars have started driving on real roads with other drivers and even carrying passengers (Uber), all without human assistance.
If that sounds amazing, brace yourself for the future because the law of accelerating returns dictates that this progress is only going to continue to increase exponentially.
Learning about supervised and unsupervised machine learning is no small feat. To date I have over TWENTYÂ FIVE (25!) courses just on those topics alone.
And yet reinforcement learning opens up a whole new world. As you’ll learn in this course, the reinforcement learning paradigm is very from both supervised and unsupervised learning.
It’s led to new and amazing insights both in behavioral psychology and neuroscience. As you’ll learn in this course, there are many analogous processes when it comes to teaching an agent and teaching an animal or even a human. It’s the closest thing we have so far to a true artificial general intelligence. What’s covered in this course?
The multi-armed bandit problem and the explore-exploit dilemma
Ways to calculate means and moving averages and their relationship to stochastic gradient descent
Markov Decision Processes (MDPs)
Dynamic Programming
Monte Carlo
Temporal Difference (TD) Learning (Q-Learning and SARSA)
Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)
How to use OpenAIÂ Gym, with zero code changes
Project: Apply Q-Learning to build a stock trading bot
If you’re ready to take on a brand new challenge, and learn about AI techniques that you’ve never seen before in traditional supervised machine learning, unsupervised machine learning, or even deep learning, then this course is for you.
See you in class!
"If you can't implement it, you don't understand it"
Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".
My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch
Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?
After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...
Suggested Prerequisites:
Calculus
Probability
Object-oriented programming
Python coding: if/else, loops, lists, dicts, sets
Numpy coding: matrix and vector operations
Linear regression
Gradient descent
WHATÂ ORDERÂ SHOULDÂ IÂ TAKEÂ YOURÂ COURSESÂ IN?:
Check out the lecture "Machine Learning and AIÂ Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)
UNIQUEÂ FEATURES
Every line of code explained in detail - email me any time if you disagree
No wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratch
Not afraid of university-level math - get important details about algorithms that other courses leave out
Apply gradient-based supervised machine learning methods to reinforcement learning
Understand reinforcement learning on a technical level
Understand the relationship between reinforcement learning and psychology
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The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into...
The Lazy Programmer is a seasoned online educator with an unwavering passion for sharing knowledge. With over 10 years of experience, he has revolutionized the field of data science and machine learning by captivating audiences worldwide through his comprehensive courses and tutorials.Equipped with a multidisciplinary background, the Lazy Programmer holds a remarkable duo of master's degrees. His first foray into...
The way you teach is amazing. However, the way you explain the code could be much better. It is ambiguous and very very top level.
Just loved the way he teaches using examples to get real experience one would face using reinforcement learning. On completion of this course I have definitely acquired great knowledge and practice for reinforcement learning in Python.
Great learning experience, the concepts are easy to put into practice by doing the code. Thank you for the course materials.
I think it is a good match
Informative and pleasant journey through reinforcement learning with Lazy Programmer. I learned a lot, earlier I just could understand it in a very limited way.
Engrossing & flow is very good. I can follow every point
This is surely a must learn reinforcement learning course for beginners and for brushing up on fundamentals. Thank you very much Lazy Programmer.
Hellish course, not all worth the money !!!
Extensive, well balanced, straight to the point content on the topic of reinforcement learning, taught in a very clear way. It could do without the slightly arrogant tone at times, but other than that, it is excellent.
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Roshan S.
Reinforcement learning in Python is an excellently designed course! For someone new to the field, this course is a must have as Lazy Programmer explains everything from scratch. I am learning reinforcement learning for the first time and this course is helping me a lot. His way of explaining reminds me of the university/college days.