What we're about

We'll go through textbooks for machine learning and data science to deepen our theoretical understanding of the subjects.

Image credit: https://deepsense.ai/what-is-reinforcement-learning-the-complete-guide/

Upcoming events (5+)

ML/AI Bookclub meetup - Reinforcement Learning

Mantelgroup Office

Happy New Year! We'll kick off with a discussion of practical examples tying in to the chapters we've dealt with so far, up to and including Temporal Difference Learning (chapter 6). Lizzie Silver and I have committed to producing some working code and we'll present it and explain the theoretical connections with the textbook. Also, hopefully, improve on the code by discussing the implementation and its alternatives! We've made some changes to how we learn the material from the books: We'll be looking at reinforcement learning using the Sutton & Barto textbook, which is freely available at http://incompleteideas.net/book/the-book-2nd.html The book is pretty theoretical (cynics might even call it "dry" ;) ), so instead of forcing ourselves through pages of abstract theory, we'll do some actual reinforcement learning first and then use the book as a reference to understand the general principles underlying what we did. With the chapters as a guide, we'll pick an exercise or workshop from the web and implement something worthwhile. We're not aiming for a lecture - the idea is to discuss the elements and ideas that were hard to grasp with the help of peers. By questioning and explaining we deepen the understanding of the topic. If you have any further questions or suggestions, shoot me a message :)

ML/AI Bookclub meetup - Reinforcement Learning

Mantelgroup Office

Happy New Year! We'll kick off with a discussion of practical examples tying in to the chapters we've dealt with so far, up to and including Temporal Difference Learning (chapter 6). Lizzie Silver and I have committed to producing some working code and we'll present it and explain the theoretical connections with the textbook. Also, hopefully, improve on the code by discussing the implementation and its alternatives! We've made some changes to how we learn the material from the books: We'll be looking at reinforcement learning using the Sutton & Barto textbook, which is freely available at http://incompleteideas.net/book/the-book-2nd.html The book is pretty theoretical (cynics might even call it "dry" ;) ), so instead of forcing ourselves through pages of abstract theory, we'll do some actual reinforcement learning first and then use the book as a reference to understand the general principles underlying what we did. With the chapters as a guide, we'll pick an exercise or workshop from the web and implement something worthwhile. We're not aiming for a lecture - the idea is to discuss the elements and ideas that were hard to grasp with the help of peers. By questioning and explaining we deepen the understanding of the topic. If you have any further questions or suggestions, shoot me a message :)

ML/AI Bookclub meetup - Reinforcement Learning

Mantelgroup Office

Happy New Year! We'll kick off with a discussion of practical examples tying in to the chapters we've dealt with so far, up to and including Temporal Difference Learning (chapter 6). Lizzie Silver and I have committed to producing some working code and we'll present it and explain the theoretical connections with the textbook. Also, hopefully, improve on the code by discussing the implementation and its alternatives! We've made some changes to how we learn the material from the books: We'll be looking at reinforcement learning using the Sutton & Barto textbook, which is freely available at http://incompleteideas.net/book/the-book-2nd.html The book is pretty theoretical (cynics might even call it "dry" ;) ), so instead of forcing ourselves through pages of abstract theory, we'll do some actual reinforcement learning first and then use the book as a reference to understand the general principles underlying what we did. With the chapters as a guide, we'll pick an exercise or workshop from the web and implement something worthwhile. We're not aiming for a lecture - the idea is to discuss the elements and ideas that were hard to grasp with the help of peers. By questioning and explaining we deepen the understanding of the topic. If you have any further questions or suggestions, shoot me a message :)

ML/AI Bookclub meetup - Reinforcement Learning

Mantelgroup Office

Happy New Year! We'll kick off with a discussion of practical examples tying in to the chapters we've dealt with so far, up to and including Temporal Difference Learning (chapter 6). Lizzie Silver and I have committed to producing some working code and we'll present it and explain the theoretical connections with the textbook. Also, hopefully, improve on the code by discussing the implementation and its alternatives! We've made some changes to how we learn the material from the books: We'll be looking at reinforcement learning using the Sutton & Barto textbook, which is freely available at http://incompleteideas.net/book/the-book-2nd.html The book is pretty theoretical (cynics might even call it "dry" ;) ), so instead of forcing ourselves through pages of abstract theory, we'll do some actual reinforcement learning first and then use the book as a reference to understand the general principles underlying what we did. With the chapters as a guide, we'll pick an exercise or workshop from the web and implement something worthwhile. We're not aiming for a lecture - the idea is to discuss the elements and ideas that were hard to grasp with the help of peers. By questioning and explaining we deepen the understanding of the topic. If you have any further questions or suggestions, shoot me a message :)

Past Events

ML/AI Bookclub meetup - Reinforcement Learning

Mantelgroup Office

Photos (3)