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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 526~550

교육 기관: Deveer B

2019년 12월 22일

Very good theory and practical approach. However, some of the assignments are not very clear while explaining the questions due to which sometimes we get wrong results.

교육 기관: Mohamed A H

2018년 10월 23일

The instructors are very professional, straight-to-the-point, and they have a nice sense of humor :)

which made the course much more interesting. Definitely recommended!

교육 기관: Mykola D

2018년 6월 9일

I really like this course. I've learned basics of ML. I've really enjoyed the presentation style. The practical part was great. I am looking forward to the next course.

교육 기관: Franklin F

2018년 3월 16일

Clear and fun instruction. The course gave relevant and tangible examples of machine learning in practice and the coding was very managable for a non-systems engineer.

교육 기관: Yeremy T

2016년 2월 15일

Great introduction to Machine Learning and the different ML methods. Assignments were not mean to be hard, but practical, which I appreciate. Great instructors as well!

교육 기관: Jagdish B P

2019년 7월 20일

This is a fantastic course. The concepts are explained so well and are followed by hands-on which helps a lot. Case Study approach really is working well in this case.

교육 기관: Dennis S

2017년 4월 28일

Great presentation of the topic and fitting complexity / depth for an introduction.

Way better then all the other courses i tried before. Great instructors and concept!

교육 기관: Zeph G

2016년 1월 1일

This is a nice introduction to the concepts that will be covered in the specialization and the power of the provided GraphLab Create ML toolbox. I highly recommend it.

교육 기관: Gwendolyn G

2015년 11월 24일

This is a really good intro course. It's not pitched at a terribly high level of difficult, but it does give you a fair amount of practice. I'm really pleased with it.

교육 기관: Satish K D

2018년 11월 25일

Very informative in basics of Machine Learning. It sets the stage for a deep dive into the topics of machine learning like Regression, Classification, Clustering etc.

교육 기관: Chengran Y

2018년 3월 2일

This course is really useful, as a overview of the whole specialization. The quiz for theory and python implementation strengthen the key points for each module/week.

교육 기관: Uday A

2017년 6월 14일

A perfect introduction to ML. Couldn't ask for more. 6 weeks of coverage is neither shallow nor too deep. Sets up the stage nicely for a deeper dive in next sessions.

교육 기관: Vaibhav O

2016년 12월 25일

Great course to begin your journey into ML

Briefly introduces each topic to give a jist about it and also provides a good starting point for using python in ML context

교육 기관: Angel G C

2015년 12월 13일

In a couple of Case Studies it gives you a wide idea about the almost unlimited potential of Machine Learning while it encourages you to learn more and more about it.

교육 기관: CO17 3 G

2020년 7월 7일

it was really amazing to learn from these mentors. They were really humble, clear and had an interesting way to teach. I would love to attend more of them in future.

교육 기관: Deleted A

2018년 9월 18일

This course gives a really easy but clear concept for machine learning with examples! I hope I can learn something further with other courses in this specialization.

교육 기관: William C

2017년 10월 22일

Fantastic course, great 'learn-by-doing' introduction to ML, really entertaining teachers kept me alert throughout each session. It was great fun and I learnt a ton!

교육 기관: Sergio B S M

2020년 7월 12일

The course is very well structured, interesting lectures with real-life applications, and the programming examples and assignments were very useful and instructive.

교육 기관: Stefan v D

2020년 2월 4일

A great foundational introduction to Machine learning concepts. Ideal for people that have some background in maths and programming but no career in this direction.

교육 기관: Prashant S

2018년 10월 19일

This is a brilliant stepping stone for Machine Learning world. Basics are being discussed and explained in a very simple manner. thanks to the teachers and Coursera

교육 기관: Shital M

2017년 11월 20일

Fantastic overview of various machine learning methods. Very interesting way of exposing concepts using case study approach which makes it more engaging and useful.

교육 기관: Fernando M P

2017년 8월 10일

This course is a wonderfull introduction to the Machine Learning. It provides a good start point which is very helpful with the other courses of the specialization.

교육 기관: Fabricio N

2016년 3월 27일

Best course in data science out there. Believe me, I did all 4 other Specialization, some of then very good, some of then no quite si, but this one is far the best.

교육 기관: Chris H

2015년 12월 24일

A great introduction. Good relevant examples and thoughtful data sets were provided for the exercises. Both lecturers were engaging and clearly knew their subjects.

교육 기관: Muhammad M

2020년 7월 21일

The course is easy and good for beginners. Specifically, case study approach is quite good and furthermore hands on practice assignments greatly improves learning.