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学生对 密歇根大学 提供的 Applied Machine Learning in Python 的评价和反馈

6,247 个评分
1,121 条评论


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....



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


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!!


376 - Applied Machine Learning in Python 的 400 个评论(共 1,104 个)

创建者 miguel c

Mar 10, 2019

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

创建者 Varga I K

Feb 25, 2019

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

创建者 Reginaldo S

Apr 07, 2020

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

创建者 Arpit S

Jun 13, 2019

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

创建者 Wixee Z

Apr 28, 2019

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

创建者 Abe G V T S

Oct 08, 2017

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

创建者 Daniel W

Jun 11, 2020

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

创建者 Sultan M A A

Nov 08, 2019

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

创建者 Felipe F

Aug 29, 2019

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

创建者 Devashish S

Sep 08, 2017

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

创建者 Bernard F

Jul 31, 2017

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

创建者 Gustavo W

Jun 19, 2017

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

创建者 Jun W

Aug 04, 2018

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

创建者 Abdoulaye B

May 10, 2020

This course was more challenging for me I was one of the best course so far I have taken.

创建者 Pulkit K

Apr 25, 2020

The content of the course was up to the standard. Please continue to make such course!!!!

创建者 Konstantinos S

Aug 15, 2017

Excellent course that really drives you hard to acquire hands on experience on the field.

创建者 Omar M M

Jul 23, 2020

Excellent course no doubt , thanks to the instructor and the team prepared the course ..

创建者 Mike F

Jul 12, 2020

Good course, includes the fundamental of machine learning and how they applied in Python

创建者 Tarun P S

May 20, 2020

Be prepared for a lot of grinding but by the end, you'll be pretty good at the material.

创建者 Jiefei W

Apr 04, 2020

Assignments provided good examples on how to select, fit and optimize a model in Python.

创建者 Sergej G

Aug 17, 2019

An amazing course, the only downside is lack of in depth unsupervised learning material.

创建者 elsa y

Oct 09, 2018

really recommend!very helpful to my study of machine learning. the material is classical

创建者 Michael I

Jul 29, 2020

Good connect between the course content, lectures and the assignments. Relvant content.

创建者 Tiberiu T

Feb 01, 2020

A comprehensive review of the most important concepts and methods in machine learning.

创建者 Daniel R

Dec 12, 2018

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