Courses tagged with "Basic Genetics" (53)

In this class you will learn the basic principles and tools used to process images and videos, and how to apply them in solving practical problems of commercial and scientific interests.

The course covers the basics: representing games and strategies, the extensive form (which computer scientists call game trees), repeated and stochastic games, coalitional games, and Bayesian games (modeling things like auctions).

This advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making), mechanism design, and auctions.

Learn about General Game Playing (GGP) and develop GGP programs capable of competing against humans and other programs in GGP competitions .

In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.

In this course, you will learn how to formalize information and reason systematically to produce logical conclusions. We will also examine logic technology and its applications - in mathematics, science, engineering, business, law, and so forth.

This course provides an introduction to the field of Natural Language Processing, including topics like Language Models, Parsing, Semantics, Question Answering, and Sentiment Analysis.

This course introduces the concepts, applications, algorithms, programming, and design of recommender systems--software systems that recommend products or information, often based on extensive personalization. Learn how web merchants such as Amazon.com personalize product suggestions and how to apply the same techniques in your own systems!

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Why write programs when the computer can instead learn them from data? In this class you will learn how to make this happen, from the simplest machine learning algorithms to quite sophisticated ones. Enjoy!

Learn about different voting methods and fair division algorithms, and explore the problems that arise when a group of people need to make a decision.

This class teaches algorithms for extracting models and other information from very large amounts of data. The emphasis is on techniques that are efficient and that scale well.

Learn a new way to approach problem solving by stating the problem and letting powerful constraint solving software do the rest. This class teaches you the art of encoding complex discrete optimization problems in the MiniZinc modeling language and then shows you how to effortlessly solve them by leveraging state-of-the-art open-source constraint solving software.

In this class, you will learn fundamental algorithms and mathematical models for processing natural language, and how these can be used to solve practical problems.

Have you ever wondered how to build a system that automatically translates between languages? Or a system that can understand natural language instructions from a human? This class will cover the fundamentals of mathematical and computational models of language, and the application of these models to key problems in natural language processing.

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research.

Networked Life will explore recent scientific efforts to explain social, economic and technological structures -- and the way these structures interact -- on many different scales, from the behavior of individuals or small groups to that of complex networks such as the Internet and the global economy.

Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well.

Learn about the historical and philosophical foundations of contemporary science. Explore cutting-edge debates in the philosophy of the physical sciences and philosophy of the cognitive sciences.

In this class, you will learn the basics of the PGM representation and how to construct them, using both human knowledge and machine learning techniques.