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返回到 实用预测分析:模型与方法

学生对 华盛顿大学 提供的 实用预测分析:模型与方法 的评价和反馈

4.1
290 个评分
55 个审阅

课程概述

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: 1. Design effective experiments and analyze the results 2. Use resampling methods to make clear and bulletproof statistical arguments without invoking esoteric notation 3. Explain and apply a core set of classification methods of increasing complexity (rules, trees, random forests), and associated optimization methods (gradient descent and variants) 4. Explain and apply a set of unsupervised learning concepts and methods 5. Describe the common idioms of large-scale graph analytics, including structural query, traversals and recursive queries, PageRank, and community detection...

热门审阅

SP

Dec 23, 2016

Fantastic course! Excellent conceptual teaching for people who already know the subject but need some more clarity on how to approach statistical tests and machine learning.

KP

Feb 08, 2016

I enjoy this course. The delivery and the course topics were very interesting. I learnt a lot and peer reviewing other people assignments is a great learning opportunity .

筛选依据:

1 - 实用预测分析:模型与方法 的 25 个评论(共 53 个)

创建者 Anand P

Feb 11, 2019

V

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创建者 Yogesh B N

Feb 20, 2019

Nice course

创建者 Shota M

Feb 24, 2016

Professor Bill Howe gives great reactions to when there are typos on the slides!

创建者 Seema P

Dec 23, 2016

Fantastic course! Excellent conceptual teaching for people who already know the subject but need some more clarity on how to approach statistical tests and machine learning.

创建者 prasad v

Nov 12, 2015

The topic the professor covers are awesome. Going from statistics to machine learning is something very awesome about this course

创建者 Shivanand R K

Jun 18, 2016

Excellent thoughts and concepts presented.

创建者 Tamal R

Feb 17, 2016

Its a great review course. Prior knowledge is necessary

创建者 Chen

Jul 20, 2016

Nive that the course covered a broad range of topics.

And good to get pushed to do some kaggle competition and peer review.

创建者 Kenneth P

Feb 08, 2016

I enjoy this course. The delivery and the course topics were very interesting. I learnt a lot and peer reviewing other people assignments is a great learning opportunity .

创建者 francisco y

Jan 19, 2016

Its Hard! but AWESOME, some much info packed in a few lectures!

创建者 Kevin R

Nov 11, 2015

Very nice assignments and content. You learn a lot when you complete all assignments.

创建者 Daniel A

Nov 23, 2015

Great course!

创建者 Sergio G

Oct 30, 2017

Excellent!!

创建者 Menghe L

Jun 12, 2017

great for learner

创建者 Yifei G

Jun 26, 2019

I can feel Prof. Howe tried to cover as much as possible and to build a foundation for both practicing as well as further study on the topics. However, I do feel it is not patient enough to give a detailed yet easy-to-follow explanation for some of the topics, and I had to do quite some self-readings to close the gap. I think it will be helpful if the course can provide some reading materials on how some of the formulas are derived (e.g. gradient descent, logistic regression etc.) as a supplement.

创建者 Bingcheng L

Aug 07, 2019

Too little people participated and long peer review time.

But the course content is good.

创建者 Artur S

Nov 24, 2015

Excellent course with amazing practical exercises!

创建者 Balaji N

Nov 16, 2015

i love it

创建者 SIEW W L

Jun 06, 2016

A quick overview of technology terms used for Machine Learning, and gentle introduction into learning through Kaggle.

创建者 Roberto S

Jun 13, 2017

Very good approach to each method; the assignments are a good test for the topics.

创建者 William L K

Jun 06, 2017

Excellent Lectures. Since the course is several years old the organization of some of the assignments needs updating. That's the only reason I gave it 4 instead of 5 stars.

创建者 Jason M

Dec 19, 2015

Excellent crash course in machine learning and introduction to the kaggle data science competitions. However, the grading system had bugs and was unable to accept two answers as correct making it very frustrating. The grader was finally fixed so next round of this course should be a better experience.

创建者 Zoltan P

Dec 23, 2015

More dynamic visualisation please, and it will be 5*.

创建者 Harini D

Aug 31, 2016

The entire course is an overview! This course will be a revision if you already know the concepts.

创建者 Nico G

Dec 22, 2015

Very interesting course. It would be useful to download slide used during videos.