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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
12,168개의 평가
2,913개의 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

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

PM
2019년 8월 18일

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,823개 리뷰 중 251~275

교육 기관: Gaurav S

2020년 5월 20일

Emily and Carlos have done a great job in preparing this course. This course is for anyone who doesnt have any background of Machine learning. The hosts have taught the course by implementing a practical approach. I have learnt a lot out of this course and i hope to complete the remainder of the courses.

교육 기관: Chengyu H

2016년 9월 16일

It is a good introduction to machine learning with cases. It explains all the big concepts in a high level, and uses all the out of box functions of graphlab to implement those ideas. Do not expect to have super detailed understanding of all the algeralisms and step by step how to do it from scratch.

교육 기관: Aashritha K

2020년 8월 30일

I found it very useful in terms of getting used to python programming, jupyter notebook and machine learning concepts. The case study approach gave me an opportunity to immediately apply the machine learning concepts learnt in the course. The course structure is very well organised to do the same.

교육 기관: Stephen M

2017년 12월 13일

Great SURVEY of use cases and methods in machine learning and an opportunity to familiarize yourself with Jupyter notebooks, Python and GraphLab Create. This is an orientation to machine learning; none of the use cases or methods are covered in great depth (that comes in the courses that follow)

교육 기관: Deepak

2016년 8월 23일

This course gives overview of what we are going o learn ahead in machine learning course. Carlos and Emily they both explain stuffs in very detail manner. IN fact it so much fun to learn when you understan thing and specially these cool stuff i hope to see some more courses on this in future. :)

교육 기관: Shuai S

2017년 12월 5일

I think this course is a quite cool fundamental Introduction. After finishing the course, you can do real things like building a MPC (Model Prediction Control) system using regression technique and so on. I fully encourage you guys joint this course for a getting started step into the ML field.

교육 기관: Aislyn N R

2016년 8월 26일

Very well presented! The tools are explained and provided in a way for genuine learning and application. The jupyter notebook assignments allow one to jump into the material, while taking detailed notes along the learning 'journey'. I am excited for all the other courses in this specialization!

교육 기관: Partha P M

2016년 12월 20일

Learned iPython Notebook which is good for Machine Learning.Helped me to understand the basics of all the ML techniques and helped me understand where to apply which ML model. This course will not teach u ML in depth , for in depth knowledge u have to take other courses in the specialisation.

교육 기관: Yogeshwar G

2017년 4월 28일

It was amazing! I cannot describe the feelings one experiences when playing with the machine learning codes. My only complaint is that I would have wanted more in the neural network/deep learning module, but I guess there will be another specialization course for that. Thank you Professors!

교육 기관: Willismar M C

2016년 8월 31일

It was a great course, showing the general applications of machine learning and great tutorial in how to implement the solutions without the technical and theoretical part of it. Also the use of IPhyton give a lot of flexibility to the material and the exercises. I really enjoyed. Thank you

교육 기관: Anindya S

2016년 1월 2일

Dr. Carlos Guestrin and Dr. Emily Fox are amazing. Needless to say, their way of teaching is absolutely brilliant and fun to learn, concepts which took me few days to learn now takes an hour or so, this is primarily due to their mastery on the subject matter and their lucid way of teaching.

교육 기관: Roberto C

2015년 10월 22일

I really liked this course (I have one week to finish, but I have enough data to judge). The professors are really pedagogic and the examples are really clear. The only thing is that I would rather have more difficult programs, I feel like that I do not have much to think to pass the tests.

교육 기관: Phuong N

2017년 6월 23일

I really love this course. After the first course i get the basic background machine learning. I can see everything that machine learning can apply. The course just easy to understand and give me one years trial graphlab lib for python which is useful for me can access machine learning .

교육 기관: Abhijit P

2017년 7월 17일

Excellent course to get you started with machine learning. Both the presenters bring a in lot of their expertise and experience to make this course fun and engaging. Lot of examples are shared which help to understand the topics in a much better way. This training is really top notch. I

교육 기관: Khandaker S M

2020년 6월 11일

Introduces you to this really powerful python library 'graphlab'. As a beginner, sometimes I found it hard to solve the programming problems. Also there should've been a video on how to install graphlab. I think this was the hardest part :v A really good machine learning course overall

교육 기관: Wan S L

2016년 6월 12일

One of the best courses I have learnt from Coursera. I love the way the lectures are presented, and how great our teachers guide us through it! I love the materials given, the projects and assignments, and the fun part interacting with teacher. Overall, five stars! Highly recommented!

교육 기관: Moez B

2017년 1월 3일

Excellent overview of machine learning and a great approach (case-study) to introducing the field. The instructor were fun and did an excellent job. Looking forward to the rest of the specialization for a deeper work with the math and algorithms behind the various techniques covered.

교육 기관: Freddie S

2016년 7월 25일

The instructors have taken great care to make "machine learning" human "learnable"! The concise unified ML framework, intuitive real-world case studies, and introductory coding exercises provide students with a very helpful "roadmap" for understanding and internalizing the material.

교육 기관: Carlos D M

2015년 12월 21일

Well-paced. Assignments are well executed. They are challenging enough to really force me to learn but not too easy that I'm feeling like I'm wasting my time.

This class in particular was somewhat high-level and left me very interested in the rest of the classes in the specialization.

교육 기관: Lingqi Z

2015년 9월 28일

A great course for beginners. Unlock the power of machine learning in a quite non - mathematical way. But even for people who are familiar with machine learning, you can learn some good pratical programming toolbox to help you prototyping or develop your machine learning application.

교육 기관: Daniel S

2015년 12월 12일

I think this course is an excellent introductory survey of the topics and technologies relevant to machine learning. The teaching method is much more than a mere regurgitation of facts and contributes to an environment where topics can be truly learned and applied in the real world.

교육 기관: Satish M G

2016년 12월 8일

This is an excellent course provided by the creators of this course. My sincere appreciation to both of them. The length of theory and practicals are very appropriate. I am very sure to continue all courses and finish them and master them. Thanks coursera for providing this course.

교육 기관: Saravana P

2015년 12월 20일

This course gave an introduction to ML concepts and applications. This course is good for absolute starters, as it doesn't scare the learner with hard core theoretical concepts. I learnt a fair bit about the overall ML scenario. Thanks to the instructors for making it fun to learn.

교육 기관: Saravanan C

2017년 5월 26일

The strategy of making people to become comfortable by first providing simple hands-on and building confidence is good. That will motivate them to stay along ALL the 6 course without getting perplexed. I see good team work! Thanks - I will strive to complete all the six modules.

교육 기관: Ashar M

2016년 10월 23일

Great course, focused on practical learning and some of the widely used applications, such as sentiment analysis, product recommendations, image recognition etc. The videos are crisp and to the point and you will appreciate the amount of knowledge they pack in a very short time.