Faculty Members Win Carnegie Bosch Institute Research Awards 2019
Three faculty members affiliated with the Machine Learning Department at CMU were awarded research awards
Eysenbach Named Hertz Fellow
Carnegie Mellon machine learning PhD student Ben Eysenbach is one of 11 students to be named a 2019 fellow out of more than 840 applicants.
Zhou Named Paul and Daisy Soros Fellow
Carnegie Mellon machine learning PhD student Helen Zhou is one of 30 students to be named a 2019 fellow out of more than 1,700 applicants.
Members Affiliated With the Machine Learning Department Win J.P. Morgan AI Research Awards 2019
J.P. Morgan AI Research just completed a round of their prestigious J.P. Morgan AI Research Awards. Faculty members Ameet Talwalkar, Ariel Procaccia and Tom Mitchell have won Faculty Research Awards, along PhD student Adarsh Prasad with a PhD Fellowship.
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Machine Learning Open House
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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 about our PhD Open House
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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.