Coursera MOOC / Non-credit 0

Machine Learning Algorithms: Supervised Learning Tip to Tail

Name: Machine Learning Algorithms: Supervised Learning Tip to Tail
Price: 99 USD
Availability: InStock

Alberta Machine Intelligence Institute

About this course

This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbours and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML. To be successful, you should have at least beginner-level background in Python programming (e.g., be able to read and code trace existing code, be comfortable with conditionals, loops, variables, lists, dictionaries and arrays). You should have a basic understanding of linear algebra (vector notation) and statistics (probability distributions and mean/median/mode). This is the second course of the Applied Machine Learning Specialization brought to you by Coursera and the Alberta Machine Intelligence Institute.

83/100

CourseAsk score

What the provider tells you: 32/45
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

implement supervised learning techniques
analyze business case scenarios
contrast data preparation steps
describe production issues in applied ML

Machine Learning #machine learning #business analysis #statistics #supervised learning #decision trees #data preparation #linear algebra #k nearest neighbors #support vector machines

$99.00

Price shown by Coursera — confirm on their site.

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