Machine Learning
Master practical machine learning with hands-on Python implementation of prediction, classification, and clustering algorithms.
Master practical machine learning with hands-on Python implementation of prediction, classification, and clustering algorithms.
This comprehensive specialization from the University of Washington provides practical experience in major areas of machine learning. Students learn to analyze large datasets, create adaptive systems, and build intelligent applications through hands-on case studies and Python programming, covering core concepts from regression and classification to clustering and information retrieval.
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English
বাংলা, Tiếng Việt, پښتو, 3 more
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What you'll learn
Build end-to-end machine learning applications
Implement regression models for prediction tasks
Develop classification systems for sentiment analysis
Master clustering and document retrieval techniques
Apply deep learning and recommender systems
Evaluate model performance and tune parameters
Skills you'll gain
This course includes:
78 Hours PreRecorded video
Case studies and programming assignments
Access on Mobile, Desktop, Tablet
FullTime access
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There are 4 courses in this program
Machine Learning Foundations: A Case Study Approach
Course 1 · 18 Hours to complete · 7 modules
Machine Learning: Regression
Course 2 · 22 Hours to complete · 8 modules
Machine Learning: Classification
Course 3 · 21 Hours to complete · 10 modules
Machine Learning: Clustering & Retrieval
Course 4 · 17 Hours to complete · 6 modules
Fee Structure
Payment options
Financial Aid
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