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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
6,544 個評分
1,168 條評論

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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351 - Applied Machine Learning in Python 的 375 個評論(共 1,149 個)

創建者 Said G

Oct 26, 2019

It was really a good experience. The content is rich and clear and the tools at our disposal are of good quality.

創建者 Dindayal H P

Jul 20, 2019

The overall course structure was very good. Also the instructor was good at his knowledge and explaination skill.

創建者 Pooja C

Jun 17, 2018

Helped me understand the fundamental concepts and practice them with assignemens. I highly recommend this course.

創建者 Janesh D

Nov 14, 2017

It was a great course. This course covered a lot of material and Professor explained every concepts very clearly.

創建者 Deepak G

Jun 24, 2020

A very nice course to get involved with the data from good resources and with great insights to draw from those.

創建者 Yuwei Y

Jun 04, 2019

I like this course very much. It focuses on ML application and it's easy to understand. Definitely recommend it!

創建者 Vasilis S

Aug 12, 2018

Great course! Assignment 4 is very interesting and allows you to apply all you've learnt in this course at once.

創建者 Ryan J

Feb 11, 2018

Incredibly insightful and helpful for a recent master's graduate looking to augment his skills on the job market

創建者 Matthias B

Aug 05, 2017

Great course, very hands-on. Maybe difficult to follow without any prior knowledge in machine learning, though.

創建者 Andrii T

Jul 13, 2020

Excellent course. I'm particularly thankful to the instructor, who was warm-hearted and explained well enough.

創建者 Liu L

Jan 03, 2019

This course provides a good introduction to using python in machine learning. It helps me to get hands on it.

創建者 Mikhail S

Aug 27, 2017

Thank you for the very well done course! It's really helpful, has a clear explanation of topics and examples.

創建者 Ahmad A

Jul 11, 2020

Excellent Course each topic is both theoretically as well as as practically explained. Really a good course

創建者 Akshay S T

May 25, 2020

Very Intuitive and helpful course for clearing concepts of machine learning and Python's SciKit Learn module

創建者 Nitin k

Apr 22, 2019

Great Course. Helped me to learn the concepts of Machine Learning and uses of respective Sklearn libraries.

創建者 Mohamed A M A

Jan 19, 2019

The theoretical part is comprehensive with an excellent balance between the theory and practical exercises.

創建者 HISHAM I A

Nov 05, 2018

Excellent collection of various types of Machine Learning Algorithms with visual demonstration and example.

創建者 Rahul S

Dec 08, 2019

This course is Beautifully crafted to cover most of the important concepts of supervised machine learning.

創建者 Christian E

Jan 19, 2019

Content and phase are very good. Very clear explanation of topic by the instructor. Appreciate it so much.

創建者 Anurag W

Jul 18, 2019

This Course really provides great learning on Advance Machine learning techniques with Python application

創建者 Matt E

Aug 29, 2017

Learned a lot in this course! Much better than the previous two and also taught by a different professor.

創建者 Alexander A

Aug 17, 2020

Excellent Course. The only one problem is the duration of videos. The codes in Jupyter are very elegants

創建者 Miguel Á B P

Jul 28, 2018

What a challenge. Incredible course, no words. Excellent pedagogy from professor Kevyn Collins-Thompson.

創建者 Alejandro R

Jul 08, 2018

Good choice for Machine Learning introduction, Data Analysis in Python and applied statistical concepts.

創建者 Mile D

Oct 17, 2017

After this course you will be able to do your own analysis using machine learning which is really great.