Machine Learning Foundations: A Case Study Approach offered by University of Washington
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Machine Learning Foundations: A Case Study Approach at University of Washington Overview
Machine Learning Foundations: A Case Study Approach
at University of Washington
Gain a comprehensive overview of Machine Learning Foundations: A Case Study Approach
Duration | 18 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course |
Course Level | UG Certificate |
Machine Learning Foundations: A Case Study Approach at University of Washington Highlights
Machine Learning Foundations: A Case Study Approach
at University of Washington
- Earn a Certificate after completion
- Financial aid available
Machine Learning Foundations: A Case Study Approach at University of Washington Course details
Machine Learning Foundations: A Case Study Approach
at University of Washington
Skills you will learn
What are the course deliverables?
- Python Programming
- Machine Learning Concepts
- Machine Learning
- Deep Learning
More about this course
- In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images
Machine Learning Foundations: A Case Study Approach at University of Washington Curriculum
Machine Learning Foundations: A Case Study Approach
at University of Washington
Welcome
Regression: Predicting House Prices
Classification: Analyzing Sentiment
Clustering and Similarity: Retrieving Documents
Recommending Products
Deep Learning: Searching for images
Closing Remarks
Machine Learning Foundations: A Case Study Approach at University of Washington Faculty details
Machine Learning Foundations: A Case Study Approach
at University of Washington
Emily Fox
Emily Fox is an assistant professor and the Amazon Professor of Machine Learning in the Statistics Department at the University of Washington. She was formerly at the Wharton Statistics Department at the University of Pennsylvania.
Carlos Guestrin
Carlos Guestrin is the Amazon Professor of Machine Learning at the Computer Science & Engineering Department of the University of Washington. He is also a co-founder and CEO of Dato, Inc., focusing on making it easy to build intelligent applications that use large-scale machine learning at their core.
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Machine Learning Foundations: A Case Study Approach
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