Machine Learning Fundamentals

MOOC
Machine Learning Fundamentals
Language
English
Duration
3 months
Certificate
Certification paid
Course by EdX
Machine Learning Fundamentals
What will you 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
About the 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.

Program
Machine Learning Fundamentals
Understand machine learning’s role in data-driven modeling, prediction, and decision-making.
Machine Learning Fundamentals
Understand machine learning’s role in data-driven modeling, prediction, and decision-making.
Machine Learning Fundamentals
Understand machine learning’s role in data-driven modeling, prediction, and decision-making.
Lecturers
Sanjoy Dasgupta
Sanjoy Dasgupta
Professor of Computer Science and Engineering UC San Diego
Platform
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All the courses on this platform are free of charge. The authors are top universities and corporations that seek to maintain high quality standards. If you do not meet a deadline for assignments, you lose points. Like on other platforms, the videos in which the theory is explained are followed by practical assignments. Courses are available in English, Chinese, Spanish, French and Hindi.
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