Concept
Reinforcement learning
Related courses (50)
FIN-423: Financial machine learning projects
The objective of this course is to acquire experience in financial machine learning by solving real-world problems. Different groups of students will work on different industry projects during the sem
PHYS-754: Lecture series on scientific machine learning
This lecture presents ongoing work on how scientific questions can be tackled using machine learning. Machine learning enables extracting knowledge from data computationally and in an automatized way.
MICRO-457: Materials processing with intelligent systems
Repeatability in laser material processing is challenging due to high-speed dynamics. To address this issue, the course provides an overview of laser theory, laser-material interaction, various types
MICRO-573: Deep learning for optical imaging
This course will focus on the practical implementation of artificial neural networks (ANN) using the open-source TensorFlow machine learning library developed by Google for Python.
BIO-620: Neuroeconomics / Decision Neuroscience
This course covers three major topics introducing: (1) fMRI methods, experimental designs and fMRI analysis; (2) recent research on cognitive and decision neuroscience in humans; (3) neuroimaging stud
CS-612: Topics in Natural Language Processing
This seminar course explores advanced topics in natural language processing through a mix of reading, reviewing, and writing academic papers.
ENG-615: Topics in Autonomous Robotics
Students will be introduced to modern approaches in control and design of autonomous robots through lectures and exercises.
EE-618: Theory and Methods for Reinforcement Learning
This course describes theory and methods for decision making under uncertainty under partial feedback.
CS-233(a): Introduction to machine learning (BA3)
Machine learning and data analysis are becoming increasingly central in many sciences and applications. In this course, fundamental principles and methods of machine learning will be introduced, analy
MATH-804: MLSTATS
ML for predictive modeling is important in both industry and research. We join experts from stats and math to shed light on particular aspects of the theory and interpretability of DL. We discuss the