Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7

stars

17,862 ratings

About the Course

Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP. Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills. Enroll now to start building machine learning models with confidence using Python....

Top reviews

Apr 17, 2020

This course was a great taster for machine learning techniques. My only recommendation would be to add more explanation on tuning techniques for models and cover more of the supporting mathematics.

Feb 1, 2020

Quite an informative course, well presented material without being overbearing for newcomers to ML. Highly recommended to everyone with prior CS experience who wants to get into AI/ML workloads.

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Aug 31, 2020

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Aug 14, 2020

Best

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Jun 13, 2020

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May 24, 2020

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good

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Good

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Dec 3, 2018

nice

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Jul 24, 2025

i’m

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Jul 25, 2024

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Nov 15, 2021

OK!

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okk

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