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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

8,050 個評分
1,471 條評論


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....




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



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.


476 - Applied Machine Learning in Python 的 500 個評論(共 1,463 個)



The instructor for this course was really good compared to the previous ones. I learnt a lot...

創建者 Yuxin W


Excellent course, with very clear lectures and useful exercises. Final project was interesting.

創建者 Mohamad F I


A good course focusing on basics of machine learning. Great for beginner with python knowledge.

創建者 Ivan R


Great course that covers the key aspects of machine learning in a manner that is easy to follow

創建者 Dmitry B


This course is the fast lane to hands-on experience with machine learning tools and algorythms!

創建者 Martin H


very excellent course, must take if you are welling to deal with data and applying ML al. to it

創建者 miguel c


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

創建者 Varga I K


Great and Strong fundamentals on machine learning without too much mathematics involved in it.

創建者 harsh J


Best Practical Course Ever Found. Learned many new things and applied them to other projects.

創建者 Reginaldo S


This course is perfect for those who wants to learning machine learning techniques in Python.

創建者 Arpit S


A Great course, the extra offered learning material helped me out to dig deep into the course

創建者 Wix Z


I can build a easy machine learning pipeline by myself after learning a lot from this course.

創建者 Abe G V T S


Great course! Very recommended! Though the assignments were kinda hard, but they are worth it

創建者 Ardong S


highly recommended course for intermediate machine learning practitioner (or also beginner).

創建者 Daniel W


Very nice course to better understand Scikit Learn and Python potential for Machine Learning

創建者 Sultan A


the course was fun and full of information to learn. very well professor. thank you so much.

創建者 Felipe F F


Excellent applied course! Very intuitive and the instructor is very kind in his explanations

創建者 Devashish S


Really hands on course and the perfect way to get to know the domain and learn ML in Python.

創建者 Bernard F


Excellent balance of theory and practical work through code samples, quizzes and assignments

創建者 Junqing Z


Really useful course. Love the talking pace of the instructor Prof. Kevyn Collins-Thompson!

創建者 Mengru Z


Quite challenging course to get started with machine learning! Interesting and worth a try!

創建者 Ishan D


Best course to learn applied machine learning and you'll be able to apply in real life too.

創建者 Gustavo W


Great course! Introduces ML algorithms using python's scikit-learn in an easy to follow way

創建者 Jun W


A very good course. The Jupyter Notebook of this course is very useful and self-contained.

創建者 john w


good course. the homework actually aligned with the lesson content. I enjoyed this course