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返回到 机器学习基础:案例研究

學生對 华盛顿大学 提供的 机器学习基础:案例研究 的評價和反饋

4.6
11,429 個評分
2,734 條評論

課程概述

Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python....

熱門審閱

BL

Oct 17, 2016

Very good overview of ML. The GraphLab api wasn't that bad, and also it was very wise of the instructors to allow the use of other ML packages. Overall i enjoyed it very much and also leaned very much

SZ

Dec 20, 2016

Great course!\n\nEmily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

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351 - 机器学习基础:案例研究 的 375 個評論(共 2,654 個)

創建者 Andrew T

Nov 06, 2015

I enjoyed this course a lot! The case study approach is very helpful to quickly understand how to apply the theory to the real world problems. The course materials are very well organized, especially the lab assignments.

創建者 Willem v G

Mar 20, 2018

Both instructors are very good at explaining the concepts of ML. Also the practical part of the course working with Python and Jupyter notebooks definitely helps in understanding the concepts and apply them right away.

創建者 Balaji S

Jun 28, 2017

The course is a perfect introduction to machine learning. I hope the upcoming course will reveal the abstraction of algorithms used in this course. The instructors are awesome. The materials are very easy to understand

創建者 Balaji C G

Jan 09, 2017

The case study approach for explaining machine learning concepts is commendable. This kind of approach will not only help in cementing the concepts but helps in making decisions when it comes to real-life applications.

創建者 Robert G

Oct 29, 2015

These instructors are among the very best I have encountered as a veteran of dozens of MOOCs. Their expertise in the subject matter, presentation and pleasant manner made this a highly pleasurable learning experience.

創建者 Abdulrazak Z

Jan 15, 2020

REAL-LIFE artificial intelligence applications. The examples were so good and real match to the reality, so in this course, I wasn't bored by theoretical information but I have seen its benefits with the code I write.

創建者 Daniel A

Sep 16, 2017

Great course covering the key models, concept and applications in machine learning. Instructors showed good pedagogy, teaching complicated concepts in ways easily understood. Requires some basic knowledge of Python.

創建者 Gustavo B

Sep 17, 2016

For me this is the best course for Machine Learning Foundations that I watch. It was challenging for me because I did the assigment with R packages. I hope on the future for doing other courses for the specialization.

創建者 Uduak O

Dec 12, 2015

Excellent course content with emphasis on real-life applications

Great teaching tools and I particularly love the teaching style of Carlos and Emily. Going on with this specialization till the very end.

Great work guys!

創建者 Soumen D

Nov 16, 2016

Love the way the subject is introduced. The course increased my interest for machine learning and also made me understand the power of machine learning first hand. Thank you, Prof Carlos , Prof Emily and entire team.

創建者 Pedro E C T

Jul 20, 2017

Un curso muy bien explicado, fácil de entender y unos profesores que consiguen mantener la atención y absorberte en el tema.

Lo recomiendo 100% para iniciarse en los modelos y entender los algoritmos simples de ML.

創建者 Brian S

Sep 27, 2017

Loved the case study approach and how it relates to real world problems. Utilizing graphlab also helped abstract away a lot of the details, but I look forward to diving deeper with the rest of the specializations!

創建者 anirban d

Aug 19, 2019

This stream along with Andrew NGs is the best ML course available in Coursera. The lectures, especially from Emily's are one of the best. It is perfect for both experienced and newbies. Thanks, Emily and Carlos.

創建者 Shekhar P

Apr 05, 2016

Awesome course ....Both Professors are very intelligent and teaching perfectly....Step by step explanation and also never feel bore because presentation styles are also very best. Thanks professors and Coursera.

創建者 Aniket R

Feb 06, 2016

The case study approach makes it fun to learn machine learning. The introduction to various topics through specific examples increases curiosity and sets the tone for the following courses in the specialization.

創建者 Alessio D M

Dec 07, 2015

I think the course is really COOL :) I know that it's really hard to cover so many topics, but I would have been curious about the area of reinforcement learning too. Perhaps mentioning MDPs and related models.

創建者 Lin V

Feb 20, 2016

Thank you very much for providing us this cool and exciting course. Thank you, Emily and Carlos. It opens a door for me and I've really enjoyed ML so far. Hope one day I could be part of the UW. All the best.

創建者 Cristina E

Feb 12, 2016

Very good explanations and well-thought out assignments and practical exploration. The usage of the proprietary GraphLab software was a minus, but since it was used just for exploratory purposes, no harm done.

創建者 Hossein N S

Feb 09, 2016

This course was very usefull tome as it was implemented in a way that it's easy to understand the core of the module and the subject.

I understand and it prepared me for the rest of the Machine Learning courses

創建者 Ethan G

Nov 23, 2015

This was a great intro course to the topic, and the instructors both make complicated concepts accessible. For example, the explanation of non-linear features in deep learning is extremely clear and intuitive.

創建者 PRAVEEN R U

Aug 23, 2018

This will be really helpful for someone who really wants to start the ML journey and not sure where to start. The content was designed well to suit people across levels and technologies. Strongly recommended.

創建者 SANDEEP

Jul 28, 2018

To define how machines can learn, we need to define what we mean by “learning.” In everyday parlance, when we say learning, we mean something like “gaining knowledge by studying, experience, or being taught.”

創建者 Adrian L

Jul 10, 2020

Friendly introduction to basic concepts and how to put them in practice to start diving into the exciting ML world that is all around us nowadays, specifically during current uncertain and challenging times.

創建者 Lokesh K

Jan 27, 2019

I appreciate the effort you kept for this online course.Actually I enjoyed learning here.But you can be little bit more detailed in the ipython notebook code explanation. Otherwise ,this is the best course .

創建者 RAMESH K M

Feb 08, 2016

Course is really taking a practical approach towards machine learning, with theory and practical classes side by side. Thanks to Course era and University of Washington for providing a wonderful opportunity.