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Learner Reviews & Feedback for Applied Machine Learning in Python by University of Michigan

4.6
stars
8,476 ratings

About the Course

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

Top reviews

MB

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Not for the faint of heart and some experience with Python, in particular Pandas, is preferred. Great overview of the different methods used in machine learning. One of the better courses imo.

SA

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- more technical materials, comparisons and better classified details should've been provided, especially to be more proportional to the assignments.

-again, subtitles were full of typos

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751 - 775 of 1,545 Reviews for Applied Machine Learning in Python

By zios s

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Nov 23, 2017

great course very useful in data science job.

By Om P

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May 17, 2020

perfect for beginners! thank you, professor!

By Pilar V

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Sep 14, 2019

Super interesting course and specialization!

By Joan P

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Nov 5, 2017

Very interesting last programming assignment

By David M

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Jul 7, 2017

Great introduction to Scikit-learn tool set.

By Danish R

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Jul 2, 2017

P.S.: This is not an easy course to complete

By Amey k

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Jan 9, 2022

best course for machine learning enthusiast

By sudipta d

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Oct 29, 2021

this course helps me to building my skills.

By roberto T

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Aug 17, 2020

Good course, especially on the applied side

By Ranjit K

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Jul 26, 2020

Great Learning with good examples and tasks

By Olivier R

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Jul 1, 2020

Highly Recommended, the Instructor is great

By 刘宇轩

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Dec 14, 2017

The last homework is great and interesting.

By Thodoris

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Oct 26, 2017

Most complete Machine learning course ever.

By MIFTAHUL J

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Nov 30, 2020

very organized and helpful course. Thanks!

By Anurag B

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Jun 8, 2019

Great Content, Great Delivery, Thumbs Up!!

By Darío A

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Jun 2, 2018

Excellent course to get into sci kit leran

By Drew O

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Oct 8, 2017

Great course. Challenging and informative.

By Mohsen

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Aug 3, 2017

I've learned a lot. Very practical course!

By Ayush R

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Nov 9, 2020

very well details of concept and learning

By Puran Z

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Jun 1, 2020

Great course. I love it, thank professor.

By MOH S

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May 19, 2020

Excellent content and perfect instructor.

By Jay G

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Mar 20, 2020

Thank you so much for this amazing course

By Yang L

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Nov 28, 2019

love the final assignment. Had great fun!

By Gustavo H d N

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Aug 31, 2019

Good balance between theory and practice.

By dan s

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Dec 30, 2017

Fantastic Course. I highly recommend it.