Machine Learning

Completed by Soubhik Rakshit

February 1, 2017

Approximately 2 months at 10 hours a week to complete

Course Certificates Completed

Machine Learning Foundations: A Case Study Approach

Machine Learning: Regression

Machine Learning: Classification

Machine Learning: Clustering & Retrieval

Machine Learning

University of Washington

4.7 (12,518 ratings)

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210K Students Enrolled

View certificate for Soubhik Rakshit, Machine Learning, offered through Coursera. Congratulations! This Certificate establishes that you have demonstrated proficiency in the exciting, high-demand field of Machine Learning through rigorous online coursework from leading Machine Learning researchers at the University of Washington. Through a series of practical case studies, you gained applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You learned to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data. Take pride in your accomplishment and welcome to the global Machine Learning community!

Course Certificates

Earned after completing each course in the Specialization

Machine Learning Foundations: A Case Study Approach

University of Washington

Taught by: Emily Fox & Carlos Guestrin

Completed by: Soubhik Rakshit by September 5, 2016

6 weeks of study, 5-8 hours/week

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Machine Learning: Regression

University of Washington

Taught by: Emily Fox & Carlos Guestrin

Completed by: Soubhik Rakshit by December 20, 2016

6 weeks of study, 5-8 hours/week

View this certificate

Machine Learning: Classification

University of Washington

Taught by: Emily Fox & Carlos Guestrin

Completed by: Soubhik Rakshit by December 29, 2016

7 weeks of study, 5-8 hours/week

View this certificate

Machine Learning: Clustering & Retrieval

University of Washington

Taught by: Emily Fox & Carlos Guestrin

Completed by: Soubhik Rakshit by January 24, 2017

6 weeks of study, 5-8 hours/week

View this certificate