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Machine Learning Foundations: A Case Study Approach(으)로 돌아가기

워싱턴 대학교의 Machine Learning Foundations: A Case Study Approach 학습자 리뷰 및 피드백

4.6
별점
11,888개의 평가
2,846개의 리뷰

강좌 소개

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....

최상위 리뷰

SZ
2016년 12월 19일

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.

BL
2016년 10월 16일

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

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,760개 리뷰 중 351~375

교육 기관: Thales P d P

2016년 1월 15일

Excellent material to introduce such a broad topic as Machine Learning. The highlight is definitely the video lectures with Carlos and Emily whom never lose sight of the didacticpurpose and target audience for the course!

교육 기관: SATYAM S

2020년 7월 26일

An amazing course with interesting content and course structure, an in-depth explanation of various machine learning concepts and multiple worksheets that require hands-on practice of the concepts taught in the lectures.

교육 기관: Jaisimha S

2016년 12월 8일

Very good course. Great material, good challenging programming assignments. Emily and Carlos are superb. --- > Wow. Amazing. Love it...now you know I'm using all the positive feature words in their sentiment analyzer!!!

교육 기관: Dinesh P

2016년 6월 28일

This course fulfills its promises. Foundations and relevant tools are introduced via case study. Both theoretical as well as practical reviews are done before leaving for next topic. All in all, good introductory course.

교육 기관: Andrew T

2015년 11월 6일

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.

교육 기관: Willem v G

2018년 3월 20일

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.

교육 기관: Balaji S

2017년 6월 28일

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

교육 기관: Balaji C G

2017년 1월 9일

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.

교육 기관: Robert G

2015년 10월 29일

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.

교육 기관: Abdulrazak Z

2020년 1월 15일

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.

교육 기관: Daniel A

2017년 9월 16일

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.

교육 기관: Gustavo B

2016년 9월 17일

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.

교육 기관: Uduak O

2015년 12월 11일

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!

교육 기관: Mehar C S

2020년 11월 16일

It was a really nice way of presenting ML concepts using Case Studies. Giving students an idea of deployment right from the start helps in thinking of an architecture of the system for any project that comes forward.

교육 기관: Soumen D

2016년 11월 16일

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.

교육 기관: Pedro E C T

2017년 7월 20일

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.

교육 기관: Brian S

2017년 9월 27일

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!

교육 기관: anirban d

2019년 8월 19일

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.

교육 기관: Shekhar P

2016년 4월 5일

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.

교육 기관: Aniket R

2016년 2월 6일

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.

교육 기관: Alessio D M

2015년 12월 7일

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.

교육 기관: Lin V

2016년 2월 20일

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.

교육 기관: Cristina E

2016년 2월 12일

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.

교육 기관: Hossein N S

2016년 2월 9일

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

교육 기관: Ethan G

2015년 11월 22일

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.