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学生对 约翰霍普金斯大学 提供的 实用机器学习 的评价和反馈

4.5
3,148 个评分
601 条评论

课程概述

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

热门审阅

MR
Aug 13, 2020

recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course

AD
Feb 28, 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

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551 - 实用机器学习 的 575 个评论(共 592 个)

创建者 Fulvio B

May 24, 2020

This course is not at the same level of the other courses I followed in the data science specialization. The lessons seem easy but when confronted with practicalities you realise you are missing practical tools. Moreover, sometimes the code is not up to date with a package and some datasets not available anymore. This creates problems with the quizzes since sometimes is not possible to reproduce one of the given options. I do not think this is acceptable for these kind of courses.

创建者 Megan P

Apr 22, 2021

This course is out of date. The videos and books are better than many Coursera classes, but I found the quizzes and projects to be a giant time suck because required packages need certain versions of R or are no longer maintained or some other nonsense. I was spending twice as much time trying to get the data and packages to work in R Studio than I was actually coding or thinking about what the quiz question was asking.

创建者 Damon G

Mar 1, 2016

The mathematics in this course are at a high level (similar to Statistical Inference) - and are presented at a pace that is challenging without significant background in the field. There is little guidance presented on the methods required. It is recommended that students source out plenty of support material (intro to statistical inference and similar).

创建者 Marshall M

Sep 23, 2017

A lot of the concepts in the course are grazed over very briefly and don't go into that much depth. In addition, some of the concepts are taught as concepts, they are taught through examples which tends to contextualize the material. Good content but could be put together in a more in depth manner.

创建者 Mehrshad E

Mar 28, 2018

This course really lack something like SWIRL. The lectures only provide a summary, which is not helpful for someone new to the machine learning. Also, the instructure tries to cover pretty much everything but not in depth; instead, I think fewer topics should be covered in depth.

创建者 Arcenis R

Feb 25, 2016

The instructions for the final project were very unclear and even though I submitted all assignments well before their respective deadlines and reviewed the required number of projects my work was not processed for a grade thereby delaying my specialization completion.

创建者 Felipe M S J

Dec 2, 2016

No es un curso en el que se aprenda demasiado.

Parece demasiado avanzado en el uso de "caret" y en vez de enseñar, parece ser que todo debe ser aprendido con anterioridad.

Todo el material adicional que se necesita en el curso, es en general contenido externo.

创建者 Jonathan O

Apr 18, 2016

I saw two main issues with this course: 1) dated lecture videos, oftentimes with R code that can't be replicated using up-to-date packages, and 2) lack of thoughtful design: example after example after example after example doesn't really teach you anything.

创建者 Pawel D

Jan 22, 2017

This course is rather bad, not well rehearsed and hastily delivered. Especially in comparison with other, in-depth course of this Specialization. The course is more of a 'caret' package review then actual Machine Learning. I learned how to use the

创建者 Michael R

Jan 19, 2016

lecture can be really unclear sometimes because lecturer breezes through the actual implementation of training/predicting: "use x, y, and z [underlines some stuff on screen]" and you're done

Also lots of mistakes/typos in lecture and quizzes

创建者 Norman B

Feb 7, 2016

This is too high level for a machine learning course. You don't exactly learn a lot about the techniques just how to use them and name them out if you're having a conversation with a person. My least favorite course in the series

创建者 Adam C S

Jul 22, 2020

This course is fairly old and it's starting to show. Quizes require you to install versions of libraries that are multiple releases back and I ended up spending more time doing that than I did building and understanding models.

创建者 Alexander R

Aug 21, 2017

Very basic, might as well just read a cheat sheet. No explanation of how or why to choose different options in a pipeline, for example, which data slicing to use (k-folds, bootstrap, etc). Just runs through how to do them.

创建者 Stefan K

Mar 10, 2017

Very shallow content - broad, but not deep. Not many assignments instead of the last one. We hear what we heard before. For the same price, Analytics Edge at EdX is far better choice for practical machine learning.

创建者 Anju K

Apr 17, 2016

Felt difficult in understanding the overall course in short duration . 1 month is not enough for this course. I request the authors to make the course much more simpler

创建者 Vincenc P

Mar 31, 2016

Course content feels upside down. You'll learn about machine algorithm specifics and caveats before anyone explains what the said algorithm actually hopes to achieve.

创建者 Timothy A

Oct 14, 2016

This is a part of the data specialization; from afar, I would not be interested in Machine Learning because of this course. I will seek other methods to learn.

创建者 Andrés M

Jul 31, 2020

It is a poor course… A lot of the materials go to Wikipedia or other sites. What is the point of a course that sends you to Wikipedia?

创建者 Jeffrey G

Sep 12, 2017

Course project was the only project work, needed more. This course should also use swirl(). Quizzes et al contained mistakes.

创建者 Michael R

Oct 3, 2019

It's a mediocre intro to some machine learning tools. I think the course materials could be drastically improved.

创建者 Philip E W J

Jan 30, 2019

Jef leek explains to fast and the theory behind the different algorithms is scarcely explained.

创建者 Allister G A

Dec 25, 2017

The course needs to elaborate more on hands on discussions.

创建者 max

Jan 18, 2017

not what I expected for a machine learning course

创建者 Yohann B

Feb 6, 2016

incomplete and not clear. extremely disappointed.