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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

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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


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


2019년 8월 18일

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 3,043개 리뷰 중 551~575

교육 기관: Sumit

2016년 7월 8일

Excellent course, gives good overview of all the different ML algorithms.

Case studies and assignments are really good and help a lot in understanding the concepts.

교육 기관: Ali A

2016년 3월 21일

This course builds a quick but engaging overview of machine learning. The structure is more than amazing, the style of teaching is very narrative and very helpful.

교육 기관: Liliana R

2016년 1월 22일

It is a great course to learn the fundamentals of Machine Learning, also Emily and Carlos are excellent tutors, they explain very well and they give good examples.

교육 기관: Vinícius N d O

2020년 10월 6일

Good course. Strongly application-oriented, intermediate level but with some basic points as well. I think the course could improve a bit on the theoretical side.

교육 기관: Gyrdymov I

2017년 11월 12일

Amazing course. It has given me good base knowledge of ML algorithms, I consider the course a "map" for further exploration of Machine Learning world. Good start!

교육 기관: Marcus V M d S

2017년 10월 1일

Thank you very much for this course! I really appreciate the effort put into the notebooks and the preparing of the data, and the graphlab library is really cool.

교육 기관: Guo X

2017년 8월 10일

the course is great. I love case study approach for the machine learning foundation. I really love to go on learning in the following parts of the specialization.

교육 기관: Ricardo J F

2016년 9월 17일

I believe it would be very useful if the authors could provide a lecture review about python commands. Specially the ones they are going to use during the course.

교육 기관: Christopher G

2016년 1월 25일

Excellent, practical introduction to the topic -- particularly by using use cases that everyone can relate to in order to understand how machine learning "works".

교육 기관: Hui Z

2020년 5월 4일

Carlos and Emily provide excellent lectures. But it would be better if correct answers and detailed explanation can be provided for each assignment in the course

교육 기관: Adarsh K

2020년 4월 10일

course and the instructors were very good.

But figuring out how to install all the softwares in windows using wsl and copying files into that was a little tricky.

교육 기관: Rohit k

2019년 7월 12일

On behalf of our customers, we are focused on solving some of the toughest challenges that hold back machine learning from being in the hands of every developer.

교육 기관: Ravi A

2016년 10월 27일

Very good starter course for Machine Learning with enough practice examples. It was really helpful for me to understand what ML is and its real time application.

교육 기관: Rafael A

2016년 2월 22일

Excellent intro course. Emily and Carlos are really great. Very good balance of depth, practical application, and above all: intuitive, thoughtful explanations.

교육 기관: Fahim K

2015년 10월 22일

This course cover all the basic fundamentals require for Machine Learning.

Doing Assignment before this were never interesting. I am enjoying the assignment part.

교육 기관: Diwakar S G

2020년 6월 6일

This course is the best course that i have learnt till now. Wonderfully designed and presented.

Thank you to carlos sir , emily mam and entire team of coursera.

교육 기관: Nagendra B R

2020년 5월 16일

The best ever course a student can have on machine learning.really enjoyed the course,thanks for all the efforts put on this course by carlos sir ang emily mam.

교육 기관: Weichang Z

2017년 7월 18일

My favourite machine learning course for a starter, not only about these fundamental knowledge, the hands on practice of Python is really helpful for a beginner

교육 기관: Andy C

2016년 2월 13일

Best bang for your buck for getting hands on experience with popular machine learning techniques. Just the right amount of difficulty for an entry level course.

교육 기관: Gireesan N P

2017년 8월 8일

Amazing Course. Recommended to anyone with basics of Python. This is one which gives overall a good coverage on state of the art approaches to machine learning

교육 기관: Ouanis S

2016년 11월 9일

Excellent course, I particularly appreciate how concepts are introduced with examples to set the terrain for the consequent courses. Will definitely recommend.

교육 기관: Robert H

2016년 9월 5일

Great introduction to machine learning concepts. I look forward to the rest of the specialization and to developing some of my own methods and supporting code.

교육 기관: Rishabh A

2020년 7월 16일

The course was too good. I really enjoyed it & have learned a lot from this course.

Thank you, Coursera for letting me have this wonderful course.

Thanks a lot.

교육 기관: Amandeep Y

2017년 11월 3일

I really liked case study approach. I think one will be able to appreciate the application of the Machine learning along with the overview of the ML concepts.

교육 기관: LEPAGE

2017년 3월 14일

As a statistician, Excellent introduction to ML!! I can't wait doing the other specializations (regression almost done, clustering and classification on-going