Coursera MOOC / Non-credit 0

Machine Learning with Small Data Part 1

Name: Machine Learning with Small Data Part 1
Price: 49 USD
Availability: InStock

Northeastern University

About this course

This course addresses the challenge of machine learning (ML) in the context of small datasets, a significant issue due to ML's increasing data demands. Despite ML's success in various fields, many areas can't provide large labeled datasets because of costs, privacy, or security laws. As big data becomes standard, efficiently learning from smaller datasets is crucial. This course, ideal for graduate students with some ML experience, focuses on modern deep learning techniques for small data applications relevant in healthcare, military, and various industry sectors. Prerequisites include ML familiarity and Python proficiency. Deep learning experience is not necessary but beneficial.

82/100

CourseAsk score

What the provider tells you: 31/45
Who stands behind it: 35/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

apply deep learning techniques to small datasets
understand the implications of small data in machine learning
develop skills relevant to healthcare and military applications

Course objectives

address the challenges of machine learning with small datasets
prepare students for applications in data-sensitive industries
build a foundation for practical implementation of modern ML techniques

Machine Learning Deep Learning #deep learning #python #machine learning #healthcare #privacy #small data #military applications #dataset training #security laws #modern techniques

$49.00

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