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Отзывы учащихся о курсе Applied Machine Learning in Python от партнера Мичиганский университет

4.6
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Оценки: 5,913
Рецензии: 1,052

О курсе

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....

Лучшие рецензии

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!!

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

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176–200 из 1,037 отзывов о курсе Applied Machine Learning in Python

автор: Vibhore G

Feb 09, 2018

From this course you will learn direct application of Machine Learning using python. You can dive into the world of machine learning. Ipython notebooks used are really helpful. Learned a lot from this course.

автор: Eunis N

May 20, 2020

This course made me learn a lot machine learning techniques by experimenting them myself. It's more than just watching the class videos and running the notebook. You need to be ready to get your hands dirty!

автор: Yingkai

Feb 15, 2019

It is definitely the best-organized, best-paced, most-worked-on course in this specialization, and from the MOOCs I have ever taken. Strongly recommend for your knowledge and career advance. Great professor!

автор: Tsuyoshi N

Oct 13, 2018

Excellent course. I liked the projects in this course to recap the theories that I learned in the lecture and examine the new knowledge that I learned by myself with reading python library documents online.

автор: Alexandre M

Feb 01, 2019

Good class, and it's very nice to have the "applied" machine learning angle (as opposed to focusing on the mathematical / theoretical underpinnings, which are only important at a much later point in time)

автор: Josh B

Feb 04, 2018

Excellent introductory course to machine learning using python. It covers the basics for the popular supervised machine learning algorithms. I'm excited to build on the knowledge this course has given me.

автор: NoneLand

Jan 22, 2018

A very practical course for machine learning. By this course, one can get familiar with sklearn and pandas basic operation! The last assignment is a challenge for me. Thanks teacher for this great course!

автор: Dongliang Z

Dec 22, 2017

Very good lecture for beginner:easy to understand.

Also good assignment: force you to use what you learned in the course.

The discussion forum is helpful when you meet difficulties in assignments and quiz.

автор: Steven L

Apr 08, 2018

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.

автор: Carlos D R

Dec 16, 2019

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.

автор: Giorgio C

Aug 25, 2017

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.

автор: Ewa L

Jun 18, 2017

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.

автор: Angelo S

Dec 21, 2018

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.

автор: Petko S

Apr 03, 2018

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!

автор: Shashank S S

Aug 19, 2017

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

автор: Michael B

Jun 19, 2017

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.

автор: PRAKHAR K J

Apr 13, 2020

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.

автор: Jens L

Aug 20, 2018

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.

автор: Amithabh S

Jun 23, 2017

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.

автор: Abdirahman A A

Jan 13, 2019

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.

автор: Indrajit P

Mar 29, 2020

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 !!

автор: jay s

Jul 15, 2017

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.

автор: Keary P

Mar 24, 2019

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.

автор: Andrew G

Aug 27, 2017

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.

автор: Tian L

Apr 20, 2020

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.