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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
6,722 个评分
1,207 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

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

筛选依据:

326 - Applied Machine Learning in Python 的 350 个评论(共 1,189 个)

创建者 Peter D

Nov 06, 2017

Nice pragmatic approach how to apply machine learning. Compelling examples, datasets and useful tips how to visualise features.

创建者 Manoj K K M

Jun 30, 2018

For applied machine learning, outstanding. It could be improved with bit more theory, which gives more insight to the concept.

创建者 SHRISH T

Aug 20, 2017

Very good course, for people who want to apply Machine Learning without worrying too much about the theoretical aspects of it.

创建者 Raga

Jun 09, 2017

Very well designed courses! There are many materials to go in depth even if you have done Python Machine Learning in the past.

创建者 Roger A G

Jun 03, 2019

Excellent course! It teaches you the basics of Machine Leaning, and merges the knowledge already acquired in the first module

创建者 Stephen

May 03, 2019

Had all the basics of Machine Learning algorithms, but they need to update the syllabus with some trending boosting concepts

创建者 Ivan Y

Oct 24, 2018

Great! loved the final project, which is a machine learning project that you can actually put on your resume and talk about!

创建者 Muhammad S

Apr 01, 2020

I am very satisfied with this course. I learnt a lot of techniques from the course that I can apply in my research project.

创建者 Hrishikesh B

Mar 14, 2019

very good course for intermediate level learners .learned a lot in such a short time.thanks to prof.Kevyn Collins-Thompson.

创建者 Bui T D

Oct 30, 2018

It is a great course with best practices. Thank you for your time and consideration. I learnt many things from your course.

创建者 Mkhitar T

Aug 13, 2020

If anyone wants to gain practical skills in Machine Learning with Python, this course for them. Thank you for this course.

创建者 Martin U

Jan 11, 2019

Tough class, learned not to give up and keep trying. Even went back and redid some quizzes in order to get a better grade.

创建者 Boyan Z

Dec 16, 2019

A very useful course that gives very good overview for the applied side of machine learning for solving various problems.

创建者 TEJASWI S

Aug 01, 2019

Concepts were clearly taught and helped me gain knowledge in techniques used in machine learning. Recommend it to others.

创建者 SIMRAN S

Sep 06, 2020

An apt course who want to become Data scientist beautiful Basics of Machine Learning which is one of major topics in it.

创建者 Oguzhan O

Jul 17, 2020

First assingment is kinda off the track with the topic mentioned in first week. overall very good and structured course.

创建者 Henri

Mar 23, 2019

Excellent course, but be ready to spend some time on debugging the automatic grader especially for the final assignment!

创建者 Sandeep S

Aug 03, 2017

Covered a lot of topics. Helps a beginner to get a good overview of the various tools and concepts on Machine Learning.

创建者 João R W S

Jul 04, 2017

Excellent course! Learned a lot both about the concepts and how to apply the methods using scikit-learn. Very good job!

创建者 JAYESH R S

Jun 27, 2020

Awesome course really loved it, especially the visualization techniques used to represent machine learning algorithms.

创建者 Nikita

Jun 13, 2020

Very good explanations. Need full attention. Quizzes and assignments are really challenging. Good learning experience.

创建者 Dave C

Oct 25, 2019

Very enjoyable, informative and I really believe I can go on and build my own ML system with confidence. Recommended.

创建者 SUDHAKAR M S

Oct 16, 2019

Great Course. Helped to understand the basics of machine learning, the algorithms and their applications using python.

创建者 Pratyush L

Sep 28, 2018

The course gives a good overview of the concepts and a great paced programming assignments to understand the concepts.

创建者 Emanuele P

Oct 25, 2017

It gives you the methods and the essential knowledge to build a learning pipeline using Python and SciKit-learn tools.