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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

8,052 個評分


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.


1226 - Applied Machine Learning in Python 的 1250 個評論(共 1,464 個)

創建者 Bharat G


Amazing Course but Please add some more theory and concepts in Neural Networking.Overall it is a good experience.

創建者 Alpan A


Very good curriculum with a hands on project. However thera are some limitations with the platform with grading

創建者 Amine T


Complete course on supervised learning

Would be nice to cover PCA and unsupervised learning in the assignments

創建者 Andres V


the final assignment was too hard compared to the other assignments and the contens given in the last module

創建者 CMC


A little dated. Overall a good introduction. The informal explanation of SVM was particularly effective.

創建者 divya p


course is very informative with hands on details, assignments and quizzes are very useful for assessment

創建者 Maxim P


Nice there could just be a bit more of a case study to see the difference and decision ways in practices

創建者 Jesús P


great course but could be improved with a better explaining of the class on board for abstract concepts.

創建者 shashank m


Very intuitive course...and carefully designed so that it does not overwhelm the students with details

創建者 ZHAI L


Compared to previous two courses in this specialization, this course need more time for self-learning.

創建者 Justin M


Great course overall. Only reason for 4 stars is some of the assignments could use a bit more clarity.

創建者 Manjeet K


Easy to learn the course, just be focussed. Its an applied ML course, not to expect any mathematics.

創建者 Ulka K


I found the dataset in the last assignment difficult to interprit. I was hoping for a simpler one.

創建者 Vishwa M


Course Content was excellent. I really learned a lot. Assignment 4 was a hassle to submit though.

創建者 Stephen R


Wish there were a little more theory, realize it's an "Applied" course but still seemed lacking

創建者 J N


Teaching by the professor is very good and i learnt every thing from scratch thankyou coursera

創建者 Pierre D


Interesting course. Last exercise allows understanding how to use ML, when you are all alone.

創建者 Michel H


helpfull, but so many information in little time. Difficult to get clarified the ideas behind

創建者 Samantha


Very great courses ! It helps to deepen my knowledge in Machine learning. Very recommend it!

創建者 Koffi K


A part from some small issues when doing the last assignment(4), Everything was all right.

創建者 Nicholas P


Good content and teacher but needs more interactivity before the final project every week

創建者 WhiteCR


Good course for practicing machine learning algorithms with Python Sci-kit Learn package.

創建者 Massimo T


The python packages used in the course are becoming outdated

adding useless difficulties.

創建者 soymilk


Contents of lecture are good but the assignments got many problems that should be fixed

創建者 Falak S


It's really a great course for the beginner to begin with the machine learning basics.