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學生對 约翰霍普金斯大学 提供的 实用机器学习 的評價和反饋

4.5
3,200 個評分

課程概述

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....

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JC

2017年1月16日

excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!

MR

2020年8月13日

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

篩選依據:

376 - 实用机器学习 的 400 個評論(共 607 個)

創建者 Siying R

2019年11月27日

This instruction is better than the last one because he can use examples that people from outside the medical world can understand. The quiz is harder than the final project. It requires students to do extra work to figure things out. I see the pattern where the instruction really is the door holder to you and you need to walk in the room and find what you need.

創建者 Jikke R

2016年8月11日

Very enjoyable and generally quite understandable introduction to machine learnings with hands-on approach through the course project. It was a bit too fast-paced and generic for my liking, but many options were offered and highlighted for finding additional learning documents and courses to be able to deepen the knowledge acquired in this course.

創建者 Sean Q Z

2016年12月11日

As the title states, very practical way to show you how this is done in R.

Most of them are lines of codes and some explanation. There are tons of details behind that and remains un-explained.

As other courses in the specialization, students need to do a lot of self-study to further understand machine learning.

But at least, learned a lot.

創建者 Charles W

2019年12月8日

I think some material might need to be revised, but I thought it was very interesting to see everybody's model building code (and perhaps that can also help me in the future).

While it is mixed with other notes, I have more detailed thoughts in this blog post: http://cdwscience.blogspot.com/2019/12/experiences-with-on-line-courses.html

創建者 Jorge E M O

2018年9月7日

The course rushes over a lot of concepts and it already shows its age - however, it's a pretty solid introduction to machine learning from a practical perspective. It will provide you with a lot of ideas for further investigation and exploration and in the end you'll end up with a wide vision of the machine learning process.

創建者 Brandon K

2016年3月30日

The lectures were great and engaging. I felt like they went too fast. Jeff says at the beginning that this is just an overview and points to some other resources. As an overview, this class works well. You can expect to learn a bit about what machine learning is and how to to do it using the caret package in R.

創建者 Oliver S

2019年7月26日

A reference solution for the quiz questions as there are in some other courses in this specialization would have been nice, since I got sometimes very different results using the newest versions of the libraries and I'd really like to know, if I made any big mistakes and it's not only because of my setup.

創建者 Lukas M

2017年10月5日

The lectures are very good to get the basic knowledge about machine learning. One suggestion is that the lectures can be longer, covering more detailed stuff and a little bit more advanced materials. Moreover, some codes are not explained clean and clear for me. Hope it would be better in the future.

創建者 Robert S

2019年9月16日

The lecture material is great, but the quiz material is in need of updating. R and it's packages have gone through many updates since the problems were written so it is sometimes difficult to reproduce their results even with running the sample codes given after getting the answer correct.

創建者 Lucas

2016年6月3日

This course allows you to implement practical solutions using machine learning algorithms without having to know the mechanisms behind the calculations in detail. Unfortunately questions in the discussion forum were quite rare and many questions were not resolved during this course.

創建者 Swapnil A

2017年6月9日

The course covers few important topics in R like cross validation, decision trees, random forest etc. which comes in very handy for a data science aspirant. It expects the participant to have a descent knowledge in R. Overall, I am pretty satisfied with this course. Thanks!

創建者 Deleted A

2017年10月25日

This course is brief but it has the 2 best ingredients for having a really decent first step in Machine Learning:

1) It covers a broad group of different algorithms

2) It provides reference material for those in which you want to get deeper.

Really good job in this course.

創建者 Yuriy V

2016年3月10日

I liked the course and found it informative, but wish there were more stuff on unsupervised learning neural network algorithms (SOMs). Learning about most used algos are great, but would also like to know other machine learning algos that are used concurrently.

創建者 Marcus S S

2017年2月25日

Great course! The hands-on approach make it very useful for one to start doing some very interesting analysis in real life! Thanks a lot! You guys could only make some efforts in updating some classes and packages used in quizzes. But the rest was great!

創建者 Rohit P

2016年11月13日

Lectures were not very detailed.

Quizzes were good and challenging, but too many times the results didn't match the answers even when the random seed was set right

Final project should have been more challenging with more models to build and compare

創建者 subrata s

2017年3月9日

Very good course. The content can be enriched with some more technical details behind the various techniques. There needs to be 1 more course on Practical Machine Learning in the specialization as 1 course is far too less for such a vast topic.

創建者 Samuel Q

2018年10月24日

Good course to get only the basics of machine learning. The assignments and quizzes are great but the lecture material is very brief and short. The references provided throughout the lectures are probably the best source of more information.

創建者 Robert W S

2016年11月21日

Great intro to machine learning. Several algorithms with some ideas on sampling and pre-processing techniques are covered. Adding a textbook as done with some of the other data science classes would help, but other resources are referenced.

創建者 Sabawoon S

2017年9月14日

Excellent course, very practical. Found the project challenging as preprocessing data required some knowledge of the limitation of the RandomForest method i.e. both train and test needs to have same classes of data with similar levels.

創建者 Kalle H

2018年6月25日

Nice course that tries to fit a lot of material into four weeks. Due to this, the material is not so deep, although pointers are given to where the student can find additional information related to each subject covered by the course.

創建者 Kamran H

2016年2月18日

Pretty good overview of how to build some types of machine learning models through the caret library in R, but not much in terms of the theoretical underpinnings or why one method is better than the other or where it is most suitable.

創建者 Brynjólfur G J

2017年9月24日

Some problems with current and old versions of packages and problems with using other packages on different operating systems. Though that did also help foster an independent research style which will help me in the future.

創建者 Chonlatit P

2018年10月20日

GREAT course! There are all base of machine learning field. The limitation is blur between basic and detail especially maths. This course, sometimes , show the maths that make you confuse if you're not familiar with them.

創建者 Emily M

2018年3月12日

This course gives an overview of a broad subject. My personal feeling is that there could have been some more indepth examples/case studies to demonstrate how to apply these methods and analyse /interpret the outcomes.

創建者 Orest

2018年1月22日

It needs more mathematical detail. Otherwise is a fairly comprehensive class, and a great tutorial on the caret package. I recommend it, if you need to refresh concepts and get some practical exposure to caret.