Name: Applied Machine Learning in Python
Brand: University of Michigan
Availability: OnlineOnly
Rating: 4.6 (1576 reviews)

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

4.6

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8,670 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

Oct 23, 2021

It was good learning Machine Learning thru Python as using Python libraries like Pandas , Tensorflow,.etc made the work easier. Hope to do my masters in Machine Learning . Happy Learning <3

Oct 22, 2020

EXTREMELY USEFUL AND GOOD COURSE, CONGRATULATIONS TO ALL THE PEOPLE INVOLVE.Honestly, I never thought I could learn so much in an online course, excited for the rest of the specialization

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