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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

4.6
5,845 个评分
1,043 条评论

课程概述

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....

热门审阅

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

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!!

筛选依据:

326 - Applied Machine Learning in Python 的 350 个评论(共 1,026 个)

创建者 Christian E

Jan 19, 2019

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

创建者 Anurag W

Jul 18, 2019

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

创建者 Matt E

Aug 29, 2017

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

创建者 Miguel Á B P

Jul 28, 2018

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

创建者 Alejandro R

Jul 08, 2018

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

创建者 Mile D

Oct 17, 2017

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

创建者 Shashwenth.M

Dec 19, 2019

Seriously THE BEST for gaining a broad knowledge about machine learning techniques in a applied manner.

创建者 Min L

Feb 06, 2019

A very good course to start journey on data science. Good combination of reading, lecture and practice.

创建者 Francesco S

Mar 20, 2018

Excellent couse, I've gained real knowledge and the lecture is very thorough! Challenging and intense.

创建者 Oumeyma F R

Dec 23, 2019

What I loved about this course is the consistency of its content and the quality of its presentation.

创建者 Zachary Q

Aug 19, 2019

Was a great class where I learned to apply existing knowledge about ML to the actual background info!

创建者 Muhammad A R

Sep 24, 2018

Covers most of the basic supervised Machine learning Algorithms in SciKit-Learn from application POV.

创建者 KylinMountain

Jun 08, 2018

It's very impressive.

I suggest If we add a kaggle competition as a overall summery, that'll be great.

创建者 Megan J

Dec 31, 2018

In depth understanding is required to complete the assignments. Challenging without being demanding.

创建者 Evan G

Jul 24, 2018

Quick way to get exposed to supervised learning algorithms. Lays a nice foundation for ML in python.

创建者 Yashar Z Z

Aug 29, 2017

This course is one of the best courses for ML. The teacher teaches concepts clearly and completely.

创建者 Yogesh

Apr 20, 2020

Course is really good. It is good to learning. But needs to add little more mathematical concepts.

创建者 Lorena G

Aug 04, 2017

Still some hard for me both the quiz and assignment, however it is interesting and worth studying

创建者 K R R

May 03, 2020

Week 2 assignment is hard to solve. My appeal is to review the questions again and make it easy.

创建者 Nitin K

Mar 11, 2019

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

创建者 Jiangming Y

Mar 04, 2018

This is an excellent course, from which I have learnt a lot about machine learning with Python.

创建者 Yuxin W

Aug 30, 2019

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

创建者 Mohamad F I

Jun 25, 2018

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

创建者 Ivan R

Aug 06, 2017

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

创建者 Dmitry B

Jul 22, 2017

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