Chevron Left
Back to Applied Machine Learning in Python

Applied Machine Learning in Python, University of Michigan

4.6
2,575 ratings
482 reviews

About this 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

By FL

Oct 14, 2017

Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!

By OA

Sep 09, 2017

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

Filter by:

465 Reviews

By Daniel Rams

Dec 12, 2018

Wonderful program, great teacher. Learned a lot and have used a bit in the real world!

By TAIBUR RAHMAN

Dec 11, 2018

i love this course

By Akash Chavan

Dec 09, 2018

Excellent Course

By Ali Fiaz

Nov 27, 2018

Excellent Course

By Fatemeh Mousavi

Nov 25, 2018

Hi

First I want to thank all the instructors and anybody that was involved in this course preparation. That was a great opportunity and I really liked that but not in all parts . I think the syllabus was a little heavy and somehow I couldn't follow that . in the programming part I needed more guide and sample .

But in general It was good and I thank you so much.

By PREDEEP KUMAR

Nov 24, 2018

ok

By Cyrus Nikko Pante

Nov 24, 2018

THE BEST!

By Choi Huijin

Nov 23, 2018

어려웠어요 ㅠㅠ

By Patrick Kaczmarek

Nov 22, 2018

Very nicely explained. Highly recommend.

By Val Anthony Balagon

Nov 20, 2018

This is a very good way to start machine learning if you're a beginner.