Kilian Weinberger is an Associate Professor in the Department of Computer Science at Cornell University. He received his Ph.D. from the University of Pennsylvania in Machine Learning under the supervision of Lawrence Saul and his undergraduate degree in Mathematics and Computer Science from the University of Oxford. During his career he has won several best paper awards at ICML (2004), CVPR (2004, 2017), AISTATS (2005) and KDD (2014, runner-up award). In 2011 he was awarded the Outstanding AAAI Senior Program Chair Award and in 2012 he received an NSF CAREER award. He was elected co-Program Chair for ICML 2016 and for AAAI 2018. In 2016 he was the recipient of the Daniel M Lazar ’29 Excellence in Teaching Award. Kilian Weinberger’s research focuses on Machine Learning and its applications. In particular, he focuses on learning under resource constraints, metric learning, machine learned web-search ranking, computer vision and deep learning. Before joining Cornell University, he was an Associate Professor at Washington University in St. Louis and before that he worked as a research scientist at Yahoo! Research in Santa Clara.
Problem‑Solving with Machine LearningCornell Course
Machine Learning
Cornell CourseProblem-Solving with Machine Learning ()
Tell me more!Online
Course Overview
This course begins by helping you reframe real-world problems in terms of supervised machine learning. Through understanding the “ingredients” of a machine learning problem, you will investigate how to implement, evaluate, and improve machine learning algorithms. Ultimately, you will implement the k-Nearest Neighbors (k-NN) algorithm to build a face recognition system. Tools like the NumPy Python library are introduced to assist in simplifying and improving Python code.
Key Course Takeaways
- Define and reframe problems using machine learning (supervised learning) concepts and terminology
- Identify the applicability, assumptions, and limitations of the k-NN algorithm
- Simplify and make Python code efficient with matrix operations using NumPy, a library for the Python programming language
- Build a face recognition system using the k-nearest neighbors algorithm
- Compute the accuracy of an algorithm by implementing loss functions
How It Works
Course Length
2 weeks
Effort
3-5 hours per week
Format
100% online, instructor-led
Course Author
Kilian Weinberger
Associate Professor
Cornell Bowers College of Computing and Information Science
Associate Professor, Cornell Computing and Information Science
Who Should Enroll
- Programmers
- Developers
- Data analysts
- Statisticians
- Data scientists
- Software engineers
Get It Done
100% Online
100% Online
Our programs are expressly designed to fit the lives of busy professionals like you.
Learn From
cornell's Top Minds
cornell's Top Minds
Courses are personally developed by faculty experts to help you gain today's most in-demand skills.
Power Your
career
career
Cornell's internationally recognized standard of excellence can set you apart.
Stack To A Certificate
Request Information Now by completing the form below.
Act today—courses are filling fast.