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미시건 대학교의 Applied Machine Learning in Python 학습자 리뷰 및 피드백

4.6
별점
8,012개의 평가
1,460개의 리뷰

강좌 소개

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....

최상위 리뷰

FL

2017년 10월 13일

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!!

AS

2020년 11월 26일

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

필터링 기준:

Applied Machine Learning in Python의 1,451개 리뷰 중 251~275

교육 기관: Steven L

2018년 4월 8일

Very practical introduction to using Python for machine learning - less focused on theory and more focused on how to use the sklearn library and proper use cases for different classifiers and regressors.

교육 기관: Carlos D R

2019년 12월 16일

The course offers you a lots fot tools the face ML problems. There are few errors in the notebooks, but everyting is well documented in the forum. Good overview to represent data and train basic models.

교육 기관: Giorgio C

2017년 8월 25일

The course is well structured and covers all the most important topics. The programming assignment could be a bit more stimulating. Overall I'd recommend this course to everyone who's interested in ML.

교육 기관: Ewa L

2017년 6월 17일

Fantastic course! Great foundation on scikit-learn. Really focused on APPLYING machine learning with just enough information about the models themselves to understand what's going on behind the scenes.

교육 기관: Eduardo B

2020년 7월 19일

Pretty good for those who are not too familiar with all the statistics that happens "under the hood" in a machine learning algorithm. The name "applied" suits very well in that way. Congratulations!

교육 기관: Angelo S

2018년 12월 20일

An excellent resource to immerse yourself into machine learning methods. Professor Kevyn explains key concepts in the most intuitive way possible. It does require some previous experience in Python.

교육 기관: Fernando T

2021년 4월 28일

Complete course about (mainly) supervised machine learning. Several classifiers and regressors and explained and compared. Appropiate assignments to test the understanding. I recommend this course.

교육 기관: SHREY S 2

2021년 11월 7일

Great experience i learned a lot in machine learning in python with different terminologies used in applied machine learning. I understand each and every topic which was told by Kevin Collins Sir!

교육 기관: Petko S

2018년 4월 3일

Extremely useful course! You really get a lot of value from it and exactly what you would expect from such course! Very entertaining and a lot of additional educational materials! Thank You a lot!

교육 기관: Shashank S S

2017년 8월 19일

the content of videos , quiz and exercise all work extremely well together towards the stated goal of the course i.e. to give the learner a good over view of how to apply ML theories into action

교육 기관: Michael B

2017년 6월 19일

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.

교육 기관: Brett S

2020년 9월 18일

Great content and good instruction. Need to fix the files in the assignments though. It's hard to keep track in the forums and frustrating go back and forth to find out why it's not working.

교육 기관: PRAKHAR K J

2020년 4월 13일

It feels good to learn something new and highly skilled demand in Engineering. Thanks to Coursera and instructor for providing such a wonderful opportunity of learning through your platform.

교육 기관: Jens L

2018년 8월 20일

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.

교육 기관: SAURAV S

2021년 10월 24일

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

교육 기관: Amithabh S

2017년 6월 23일

Excellent course for someone who already has some knowledge of python but not quite familiar with machine learning. This course will teach you the application of machine learning in python.

교육 기관: Abdirahman A A

2019년 1월 13일

In depth course that covers a lot in a short amount of time. If you take some extra time to delve deeper into these topics, you can ensure a great overview of machine learning with python.

교육 기관: Marcin K

2021년 9월 11일

Quite detailed; good instructional material about most ML models and evaluation metrics of models, cross validations, grid searches, precision and recall curves etc. Excellent assignments

교육 기관: Diego A L B

2020년 10월 22일

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

교육 기관: RAMANA V S B

2022년 2월 24일

its a very great course i have ever seen, because it a applied ML it will avoid all waste of theory and statistics and complete focus on main points and coding part within very less time

교육 기관: Indrajit P

2020년 3월 29일

Very well structured and informative course ! All the lectures are concise and give enough context for self-exploration. The assignments provide are a good hands-on experience as well !!

교육 기관: jay s

2017년 7월 15일

Excellent lectures, good exercises to reinforce the material, and absolutely loved the explanations of the sophisticated mathematical models that made them more lucid and easy to digest.

교육 기관: Keary P

2019년 3월 24일

Great for high level concepts and practical applications of machine learning. After taking this course I feel more confident in my ability to work on real world machine learning tasks.

교육 기관: Andrew G

2017년 8월 27일

A lot of techniques packed into a relatively short course. Weeks 2 & 4 are noticably tougher than the other two, so allow plenty of extra time for assignment and quiz in those 2 weeks.

교육 기관: Tian L

2020년 4월 20일

it is a great course that covers the most important basics of the "traditional" machine learning and helps me build a solid foundation for more advanced machine learning topics later.