Among the topics considered are: data cleaning, visualization, and pre-processing at scale; principles of parallel and distributed computing for machine learning; techniques for scalable …

Carnegie Mellon University, Pittsburgh 2025 Spring: Convex Optimization (10725) 2024 Fall: Convex Optimization (10725) 2024 Spring: Convex Optimization (10725) 2023 Fall: Convex …

Education Associate: Daniel Bird, (dpbird [at] andrew [dot] cmu [dot] edu), Machine Learning Department. When/where: GHC 4401, 03:30-04:50PM, Mondays and Wednesdays. …

MLG 10405 at Carnegie Mellon University (CMU) in Pittsburgh, Pennsylvania. Large datasets pose difficulties across the machine learning pipeline. They are difficult to visualize and …

We strive to recreate that communal atmosphere among students and instructors. 10405 at Carnegie Mellon University for Spring 2018 on Piazza, an intuitive Q&A platform for students …

10-417 is undergraduate level and 10-617 is graduate level. Graduate level students will have slightly more work to do than undergraduate level students. If students in 10-417 would like to …

Machine Learning with Large Datasets. CMU-10-605 has 10 repositories available. Follow their code on GitHub.

2020年10月31日 · Definitely, a great intermediate level ML course if you want some challenge, as most of the rudimentary stuff will only be briefly reviewed most of the time. For pre-reqs, check …

Implement a general framework for developing gradient-descent optimizers for machine learning applications. Explain the differences between, and recognize potential applications of, …

Among the topics considered are: data cleaning, visualization, and pre-processing at scale; principles of parallel and distributed computing for machine learning; techniques for scalable …