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

4.6
stars
8,585 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

S

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

FL

Oct 13, 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!!

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451 - 475 of 1,562 Reviews for Applied Machine Learning in Python

By Mikhail S

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Aug 27, 2017

Thank you for the very well done course! It's really helpful, has a clear explanation of topics and examples.

By NAMAN M 2

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Jan 18, 2023

This course helped me a lot on how can we do so much interesting things using machine learning using python.

By Ahmad A

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Jul 11, 2020

Excellent Course each topic is both theoretically as well as as practically explained. Really a good course

By Akshay S T

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May 24, 2020

Very Intuitive and helpful course for clearing concepts of machine learning and Python's SciKit Learn module

By Nitin K

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Apr 22, 2019

Great Course. Helped me to learn the concepts of Machine Learning and uses of respective Sklearn libraries.

By Mohamed A M A

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Jan 19, 2019

The theoretical part is comprehensive with an excellent balance between the theory and practical exercises.

By HISHAM I A

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Nov 5, 2018

Excellent collection of various types of Machine Learning Algorithms with visual demonstration and example.

By Thomas S

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Jun 21, 2021

A very good review of important fundamental concepts in Machine Learning focusing on the usage of Sklearn.

By Rahul S

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Dec 8, 2019

This course is Beautifully crafted to cover most of the important concepts of supervised machine learning.

By Chris E

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Jan 19, 2019

Content and phase are very good. Very clear explanation of topic by the instructor. Appreciate it so much.

By Lari L

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Jul 3, 2021

The course gives deep knowledge on the subject as well as best practices and strong practice assignments.

By abdelrahman a

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Dec 9, 2020

the most interesting thing in the course was treating the students as if they are already data scientists

By Anurag W

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Jul 18, 2019

This Course really provides great learning on Advance Machine learning techniques with Python application

By Matt E

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Aug 29, 2017

Learned a lot in this course! Much better than the previous two and also taught by a different professor.

By Fettah K

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May 9, 2021

Taking these lessons from some of the world's most prestigious universities and professors is priceless.

By Alexander A

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Aug 16, 2020

Excellent Course. The only one problem is the duration of videos. The codes in Jupyter are very elegants

By Miguel Á B P

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Jul 28, 2018

What a challenge. Incredible course, no words. Excellent pedagogy from professor Kevyn Collins-Thompson.

By aerr96

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Jul 8, 2018

Good choice for Machine Learning introduction, Data Analysis in Python and applied statistical concepts.

By Mile D

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Oct 17, 2017

After this course you will be able to do your own analysis using machine learning which is really great.

By Allyson D d L

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Dec 3, 2021

Another good course of the specialization. The videos are a little boring but the assignments are good.

By Shashwenth.M

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Dec 19, 2019

Seriously THE BEST for gaining a broad knowledge about machine learning techniques in a applied manner.

By Min L

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Feb 6, 2019

A very good course to start journey on data science. Good combination of reading, lecture and practice.

By Mikhail E

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Sep 22, 2020

Great course, though was a bit difficult for me, as I wasn't very familiar with math side of the issue

By Francesco S

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Mar 20, 2018

Excellent couse, I've gained real knowledge and the lecture is very thorough! Challenging and intense.

By OUMEYMA F

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Dec 23, 2019

What I loved about this course is the consistency of its content and the quality of its presentation.