Leila Wehbe Wins Google Faculty Research Award 2018
Google Research just completed another round of their prestigious Google Faculty Research Awards. The Machine Learning Department at Carnegie Mellon University is proud to announce that faculty member Leila Wehbe won a Google Research Award in computational neuroscience.
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Machine Learning Open House
For Accepted PhD Students
March 5 &6, 2019
We hope you are able to visit us for our Machine Learning Open House which begins on March 5, 2019 at 9:30AM.Learn more
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What is Machine Learning?
A message from Manuela Veloso - Herbert A. Simon University Professor
Machine Learning (ML) is a fascinating field of Artificial Intelligence (AI) research and practice where we investigate how computer agents can improve their perception, cognition, and action with experience. Machine Learning is about machines improving from data, knowledge, experience, and interaction.
Machine Learning utilizes a variety of techniques to intelligently handle large and complex amounts of information build upon foundations in many disciplines, including statistics, knowledge representation, planning and control, databases, causal inference, computer systems, machine vision, and natural language processing.
AI agents with their core at Machine Learning aim at interacting with humans in a variety of ways, including providing estimates on phenomena, making recommendations for decisions, and being instructed and corrected.
In our Machine Learning Department, we study and research the theoretical foundations of the field of Machine Learning, as well as on the contributions to the general intelligence of the field of Artificial Intelligence. In addition to their theoretical education, all of our students, advised by faculty, get hands-on experience with complex real datasets.
Machine Learning can impact many applications relying on all sorts of data, basically any data that is recorded in computers, such as health data, scientific data, financial data, location data, weather data, energy data, etc.
As our society increasingly relies on digital data, Machine Learning is crucial for most of our current and future applications.