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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
4,264 個評分
741 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

篩選依據:

76 - Applied Machine Learning in Python 的 100 個評論(共 723 個)

創建者 Fabiano R B

Mar 08, 2019

The course is a great overview of the basic algorithms that every machine learning practitioner should know. Since it has a limited amount weeks to cover such a broad subject, you will have to dig a little deeper by yourself. I found the reading material also very interesting. The final project is awesome and it will definitely make you experiment what is exactly what a Data Scientist should do.

創建者 miguel c

Mar 10, 2019

Great collection of applied Data Science concepts, worked examples and challenges using python

創建者 Andrew

Mar 11, 2019

Really well explained theory without too much of a mathematical deep dive that provides a perfect set up to learn about machine learning from a purely math/stats perspective through Andrew Ng's Machine Learning course or self study

創建者 Harsh S

Mar 10, 2019

Great content

創建者 Nitin K

Mar 11, 2019

Well structured course that gave a good insight on applying Machine learning to real life cases.

創建者 Qiaochu S

Mar 11, 2019

This course has been really helpful to me! All the contents we need to grasp each week were well-designed and the assignments are easy, interesting and enlightening.

創建者 Oliver O

Mar 11, 2019

Great course!

創建者 PHAM A T

Mar 12, 2019

excellent course

創建者 Hrishikesh B

Mar 14, 2019

very good course for intermediate level learners .learned a lot in such a short time.thanks to prof.Kevyn Collins-Thompson.

創建者 Farzad E

Mar 14, 2019

Assignments and quizzes help you a lot in consolidating the concepts. However, some questions in quizzes are tricky but not in a way that really adds to your understanding of the topic. Overall a pretty good course. (4.5/5 is the rating I would give)

創建者 Jose Á P L

Mar 17, 2019

Muy buen curso para iniciarse en el machine learning

創建者 John H E O

Mar 16, 2019

I truly enjoyed this course.

創建者 ANUBHAV K

Mar 17, 2019

very good course

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.

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 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 Henryk S

Dec 28, 2018

I have been confidently guided through the complexities of Machine Learning through perfect mix of lectures and reading materials. Quizes and programming assignments served as very helpful tool to zoom in on specific details which in further assignments will make the difference between success and failure.

創建者 Mohamed A H

Dec 15, 2018

Awesome course!

Stick till the end of it, and you'll never regret it.

You're gonna have a lot of fun especially in the last week, don't skip the optional readings of this week ;)

創建者 Syam P N

Dec 17, 2018

Excellent course. Was very helpful

創建者 Samuel E G G

Dec 17, 2018

Fantastic. Though the teacher is not as good as the first one.

創建者 Christian L

Mar 21, 2019

Very good hands-on course to explore the implementation of the major ML algorithms with Python - Probably more valuable with prior general ML knowledge

創建者 Dingqiang Y

Mar 22, 2019

Good introduction with python tools.

創建者 Rohit M S

Mar 22, 2019

The Course is amazing. you get to learn a lot