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Foundation Subscription > Data Science > Unsupervised Learning: Real-Life Applications
Course Description
In this course, you will solve a real-world case study by implementing three different unsupervised learning solutions. Using different kinds of clustering techniques, Pandas dataframes, and data visualization, you will explore how to use unsupervised learning to comprehend data in order to make informed decisions.
Requirements
  • There are no pre-requisites for this course.
Instructor:
Hyatt Saleh; Samik Sen
Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. Samik Sen is currently working with R on Machine Learning. He has done his Ph.D. in Theoretical Physics. He has Tutored Classes for High-Performance Computing postgraduates and Lecturer at International Conferences. He has experience of using Perl on data, producing plots with gnuplot for visualization and latex to produce reports. He, then, moved to finance/football and online education with videos.