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Learner Reviews & Feedback for Supervised Machine Learning: Classification by IBM

4.8

stars

426 ratings

About the Course

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. By the end of this course you should be able to: -Differentiate uses and applications of classification and classification ensembles -Describe and use logistic regression models -Describe and use decision tree and tree-ensemble models -Describe and use other ensemble methods for classification -Use a variety of error metrics to compare and select the classification model that best suits your data -Use oversampling and undersampling as techniques to handle unbalanced classes in a data set Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting. What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....

Top reviews

Nov 7, 2020

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

May 16, 2021

Fantastic presentations and detailed course material make this course really worth it!

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76 - 86 of 86 Reviews for Supervised Machine Learning: Classification

By Poke v

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May 15, 2022

Maybe tasks within the weeks lesson could be helpful to build a powerful knowledge.

By Ashraf Z

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Jul 24, 2023

Excellent content. Great, but intense instruction/videos.

By Michael M

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Jun 15, 2022

the material in the last week felt rushed

By Venkadesh R

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Sep 26, 2024

Really worthable

By AMAR C

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Mar 3, 2024

Great con

By Muhammad T K

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Aug 14, 2025

good

By Mohamed E

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Jan 8, 2023

The instructor was very good in drilling deep in the code snippets, explaining what every line does clearly, but on theoretic side of every algorithm, I see the handling was poor, lacks the depth and clarity, many times I looked at an external sources to understand how a model works.