Learner Reviews & Feedback for Machine Learning with Python by IBM

4.7

stars

17,973 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

Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

Jun 3, 2020

In peer graded assignments, if someone is grading any peer below passing criteria then it must be compulsory to let the learner know his mistakes or shortcomings because of which he does not graded.

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Jan 12, 2020

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あ