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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
11,503개의 평가
2,756개의 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

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.

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

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,670개 리뷰 중 326~350

교육 기관: piyush s

Nov 01, 2015

Excellent course. I would have preferred sample code with Skitlearn and other Python packages as well because I believe still 95 % of the people use those. I liked the Sframe but I don't see right now many people using it in industry.

교육 기관: Leonardo T L

Aug 01, 2020

The course has an excellent approach to ML theory and practice. The TuriCreate Framework helps to increase the learning speed and depth of the classes. Congratulations to the Professors and I'm excited to continue the specialization.

교육 기관: Michael H

Jul 21, 2016

Really great introduction to machine learning and the various methods used. I really liked the length/structure of the lectures and found the assignments to be fun. I also really liked the dynamic the presenters have with each other.

교육 기관: Daniel V

Mar 27, 2016

An easy, not simple, but humorous approach to a broad topic with practical samples that you can build on for further studies. Good for newbies as well as a fresh up for advanced applicants. Looking forward to the follow up courses.

교육 기관: Andrew R

Jan 19, 2016

Great overview of different machine learning techniques. You don't learn much about implementing the individual techniques in this class, but you get a broad overview of many different techniques, which is the point of this class.

교육 기관: Miguel R

Jun 04, 2019

Muy útil para empezar a conocer los conceptos básicos de machine learning, con casos comprensibles y útiles a través de python.

Los vídeos son muy explicativos y la corta duración de cada uno permite adaptarlo a cualquier horario.

교육 기관: Ganesh K

Feb 10, 2019

Learning things with good use cases always lot better. This course really helped a lot to understand machine learning clearly. Throughout this course the explanation of the concepts are so clear and assessments are so intuitive.

교육 기관: Thomas K

Apr 01, 2018

very nice, no bull-shit introduction into main concepts from a practical perspective. It showed both easily exploitable possibilities in the field of ML as well as the outline of a huge horizon which might reach far beyond this.

교육 기관: jose l v

Dec 05, 2015

This is a very practical an easy way to understand what is behind the ML world. Also, there are a set of tools in this course that would let you implement basic smart applications. I am ver pleased for being part of this course.

교육 기관: Deleted A

Sep 16, 2016

I really enjoyed this course. The case study approach and the IPython hands-on gave a good understanding of the concepts discussed in the lecture videos. I'm looking forward to complete the specialization. Highly Recommended!!

교육 기관: Patrick N

Feb 18, 2018

I enjoyed this course as a high-level overview of the basics of machine learning. While I liked the use of Jupyter and Python in general, I would have preferred that the course use scikit-learn. Overall, solid and fun course!

교육 기관: Adil A

Dec 15, 2017

People who likes top-down learning approach should start ML from this course.

Instructors explain basic overview then follow with interesting practical tasks that makes you understand the topic much better.

Highly recommended.

교육 기관: Gustavo S

Oct 30, 2016

Very cool course. I can say is the best course for intro to a big science called machine learning, have a lot of good real life examples, with gread mathematical understaing of how things works, i thinks is really cool course

교육 기관: Varun S

Feb 08, 2016

It was indeed a very well designed course that not only gave a great overview of various machine learning techniques, but also gave hands-on experience in implementing those techniques. Loved Dato. GraphLab Create is awesome.

교육 기관: Sergey T

Jan 03, 2016

It was instructive, easy to follow and fun to learn! Great thanks to Carlos Guestrin and Emily Fox for creating this excellent course! And thanks Coursera for making the high quality educational content available to everyone.

교육 기관: ENZHE L

Oct 15, 2017

A very great course !!!!! Two teachers are doing a good job. They use a kind of practical way, case-study, to teach me lots of practical machine learning knowledge. I will learn the next three courses in this specialization.

교육 기관: Farrukh N A

Dec 16, 2016

I like the approach the course is designed on, starting with basic know how about all machine learning techniques. Later on dedicating a course on each individual approach. I am looking forward to complete my specialization

교육 기관: Massimiliano C

Jul 22, 2017

very good course, complex topics explained through intuitive and practical use cases, in short time provides an overview on Machine Learning and gives the student the chance to go in depth if necessary.

I liked it very much.

교육 기관: Kenneth L

Aug 30, 2016

An excellent overview of Machine Learning. Whether catching up with nascent developments in the recent years or first diving in, this class provides a stable, well rounded and well thought out starting point on the subject.

교육 기관: Enrique d P

Feb 18, 2018

Great! I found it really interesting! It's a great introduction to Machine Learning, different areas, solutions and applications. You can apply different methods to real data, but you only need basic programming knowledge,

교육 기관: Robin H

Mar 20, 2017

Very essential knowledge about how to get on track of ML and it did very handy for the beginner, who has qualified with the criterions of class candidate. Thanks for the effort in the class arrangement and online teaching!

교육 기관: Thales P d P

Jan 15, 2016

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

Jul 26, 2020

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

Dec 08, 2016

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

Jun 28, 2016

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.