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學生對 密歇根大学 提供的 Applied Machine Learning in Python 的評價和反饋

4.6
4,338 個評分
752 個審閱

課程概述

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....

熱門審閱

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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76 - Applied Machine Learning in Python 的 100 個評論(共 735 個)

創建者 Michael T B

Dec 19, 2018

Great class! I had fun learning many new things in this course. The professor did a very good job at taking a complex subject and making it simple and easy to understand. The code and assignments were straightforward and not overly difficult. The real quizzes/tests in this course were appreciated as this felt more like a "real class" where one can really learn a lot. One of the best online classes that I have taken.

創建者 Romel C B

Dec 19, 2018

Me gusto muchísimo, los temas, la dinámica para el aprendizaje y el trabajo final

創建者 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.

創建者 George G

Dec 23, 2018

Awesome course

創建者 Nithin R

Dec 25, 2018

contents are good.

創建者 Phillip L C

Dec 25, 2018

Great course - balanced and very revealing for direct application.

創建者 SURENDRA O

Dec 25, 2018

The course was very well designed. The pace of the lectures are perfect unlike other course when the instructor moves very fast.

創建者 Akash C

Dec 09, 2018

Excellent Course

創建者 Daniel R

Dec 12, 2018

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

創建者 John D L C

Dec 27, 2018

This is an excellent course.

創建者 Mehmet F C

Dec 27, 2018

good one to quickly start learning ML - covering models, what they do, and how to tune them. Not going deep into the "how" models work.

創建者 Sooraj S

Mar 31, 2019

Good introduction to Machine Learning and implementation in Python.

創建者 Surya P M

Apr 01, 2019

complex topics are explained in a simple way. coding assignments, quiz helped a lot to learn and apply numerous machine learning concepts perfectly.

創建者 LENDRICK R

Apr 07, 2019

A ton of learning, a challenging & rewarding course, the final assignment incorporated concepts & techniques from the first and second courses and gave me a clearer understanding of choosing and implementing machine learning algorithms. :-)

創建者 Maxwell S d C

Apr 09, 2019

One of the best courses ever! Plenty of things to learn, to evolve. Superb!

創建者 Min L

Feb 06, 2019

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

創建者 Sumit M

Feb 19, 2019

This is a very good course about How to apply Machine Learning but I think before taking this course the student should take the Andrew Ng machine learning course by Stanford University to Learn the Important Mathematics behind the ML algorithms

But Enjoyed this course a lot

thank you

創建者 Manik S

Feb 08, 2019

Optional references to the inner workings should be provided. For example how Decision Trees are trained and how the best division is decided.

創建者 Darius T

Feb 19, 2019

Great course for learning how to apply Machine Learning algorithms with Python.

創建者 TAIBUR R

Dec 11, 2018

i love this course

創建者 Roberto L L

Jan 26, 2019

Awesome Course, I learned a lot of tools from Machine Learning

創建者 H.-M. F C

Jan 26, 2019

The course ire great and illustrates many useful topics. The only thing it needs to improve is about the assignment 4 which requires more information to solve the problem, in particular, people who deal with the complete machine learning problem.

創建者 Kristin A

Jan 13, 2019

Great intro to the tools of machine learning in Python

創建者 Lewis M

Jan 13, 2019

Very good course for either an introduction to machine learning or to refresh old skills. It's also very good at putting emphasis on topics that data scientists may overlook / not pay much attention too, so having this as a reminder to look deeply into each algorithm and its application or limitations is incredibly helpful.

創建者 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.