5 Insanely Actionable Steps to Your MS Abroad [LIVE Webinar]
Learn action-by-action 5 steps for your MS abroad using our proven "5-Keys" Formula.
“I was hunting everywhere for scholarship. I couldn’t believe when I learnt about a well-defined process to get scholarship. It works because I got scholarship!”, - Jayanth Barman, Currently pursuing MS at John Hopkins University, USA
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Hosted by: Manish (IIT Kanpur & IIM Calcutta) & Pooja (Placed 1200+ students abroad)
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About this course
Do you want to build systems that learn from experience? Or exploit data to create simple predictive models of the world?
In this course, part of the Data Science MicroMasters program, you will learn a variety of supervised and unsupervised learning algorithms, and the theory behind those algorithms.
Using real-world case studies, you will learn how to classify images, identify salient topics in a corpus of documents, partition people according to personality profiles, and automatically capture the semantic structure of words and use it to categorize documents.
Armed with the knowledge from this course, you will be able to analyze many different types of data and to build descriptive and predictive models.
All programming examples and assignments will be in Python, using Jupyter notebooks.
What you’ll learn
- Classification, regression, and conditional probability estimation
- Generative and discriminative models
- Linear models and extensions to nonlinearity using kernel methods
- Ensemble methods: boosting, bagging, random forests
- Representation learning: clustering, dimensionality reduction, autoencoders, deep nets
Meet the instructor
Professor Computer Science and Engineering
University of California San Diego