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

4.6
stars
8,495 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

FL

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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!!

JL

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Concise and clear presentation of the material with the majority of time focused around using TDD to learn and practice concepts through developing solutions to open ended coding challenges.

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1501 - 1525 of 1,549 Reviews for Applied Machine Learning in Python

By Pakin P

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Jan 10, 2020

How can i pass without reading discuss about problem with notebook

By Hao W

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Aug 27, 2017

The homework is too easy to improve our understanding of ML

By M S V V

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Jun 29, 2020

Too much of information compressed within a short span.

By José D A M

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Jun 21, 2020

Too fast, yet too difficult. Needs deeper explanation.

By Navoneel C

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Nov 21, 2017

Nice and Informative but not practically effective

By Priyanka v

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May 8, 2020

if it is more detailedthen it will be more useful

By Numan A S

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Jan 8, 2024

update week 3 assignment. no clear instruction

By Sameed K

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Mar 15, 2018

have to figure out a lot of things on you own.

By Andy S

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Jun 4, 2019

It could have been better with more examples.

By Syed S

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Apr 12, 2020

The explanation could have been much better.

By Sagar J

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Mar 21, 2021

Good start but i was very boring later on.

By Jeremy D

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Jul 10, 2017

The topics were good, but too many were d

By Ryan S

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Dec 12, 2017

Homeworks are inconvenient to submit

By PIYUSH A

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May 16, 2020

The narration was a bit boring.

By shreyas

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Jun 29, 2020

Teacher wasn't very good

By Abir H R

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Jun 30, 2020

very long videos

By Wojciech G

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Oct 28, 2017

To fast paced.

By PRAGATHI S P 2

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Apr 10, 2022

dufufu

By TANMAY H B 2

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Oct 29, 2021

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By Eduardo A R O

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Aug 4, 2022

I didn't like the course very much, I was expecting more details in the coding part, but I only watched Mr. Collins-Thompson reading the code without making a deeper description of it, by compairing it with the two previous courses this one hasn't been as well as the others. Fortunately, I found it on free with my MOOC but if you have to pay for it, I trully recommend you to buy the Andrew Ng's course available on Coursera as well.

Finally I would like to say that this course was developed in 2017 or 2018 and it hasn't been changed or updated, you can find MANY mistakes on the labs at the end of each week, so if you're going to make the labs, I recommend you to take a look a the forums first instead of go ahead with the first ones, or maybe you're going to take 0/100 in each evaluation. So please update it, and maybe post the slides of each lesson, that will help on each exam wich are difficult for the way the lessons are taught.

By Aarya P

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Sep 30, 2020

Really disappointed with the course ...you may ask why??

The first thing is the instructor , super boring. The instructor (with all due respect) was very dry and the lectures were super uninteresting. When he keeps on talking code, but doesn't really explain stuff. The material and lectures were dry and colorless.

Me without having good statistics background had huge difficulties understanding the concepts. Please i recommend everyone to have good knowledge in statistics before starting the course. ABSOLUTELY NOT THE BEGINNER LEVEL AND NEITHER INTERMIDIATE LEVEL .the course is quiteeeee difficult.

You also need to have a lot of self study , which i am not a big fan of. I hope they make the course more fun rather than a man constantly talking on the screen .

By Daniel J

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Apr 30, 2021

I found this course quite challenging to complete. The assignments are difficult (which is good, they are practical and I enjoyed them) and only a fraction of things is explained in the videos. I really found much better learning materials around the web (and for free!). For applied machine learning course, I would expect more practical videos. Also the process of submitting assignments is really frustrating, I spent half the time correcting errors that were not related to the assignment objective. If this course was not part of specialization, I would not complete it.

By Douglas H

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Apr 10, 2021

Lectures are good but they expect you to extract too many fine details from them in order to pass the quizzes and assignments. You'd have to watch these oral lessons ten times in order to pass the tests, which are needlessly nitpicky.

By Sebastiaan B

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Apr 16, 2023

Nice course, but from the discussions in the forums, there seems to be an issue with the grading that several users report. I see no responses from the last three month from faculty. This leave affected users (including me) blocked.

By Oswaldo C

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Aug 22, 2020

Los videos no son suficientemente extensos ni para explicar el código, ni para explicar la teoría detrás de los algoritmos, se queda a medio camino de los dos siendo insuficiente en ambos casos