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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
9,910개의 평가
2,375개의 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

PM

Aug 19, 2019

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.

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.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,295개 리뷰 중 251~275

교육 기관: Zachary C

Apr 30, 2017

A great primer on the various high level concepts in machine learning and some general applications as well as good quick intro to graphlab create. I was originally apprehensive to use another data science tool outside of panadas, but now think graphlab create is even better.

교육 기관: Miguel A P L

Nov 28, 2016

Before taking this course I would not consider the topic as something that one could learn by himself.

The Course has opened my mind and has showed me that there is a lot to learn and study in order to fully master ML and AI in order to use it in the applications we can build.

교육 기관: Gurunath M K

Sep 30, 2019

It was truly informative course. At the end of the course, I am sure I can say I know the all the key concepts behind Machine Learning. In near future, my focus will be be try to implement in relevant use-cases around. Thanks Accenture LKM and Coursera for facilitating this.

교육 기관: Supriya N P K

Dec 09, 2015

Its a very basic course and a good start to learn Machine Learning.

Course was pretty easy to follow and the real world examples helped to visualize the applications of Machine Learning. Its highly recommended for the students who are completely new to the Machine Learning.

교육 기관: Puppala A S

Apr 28, 2020

The course was awesome and i am willing to learn all the courses present in this specialization.Both the tutors are great and their explanation was incredible . Actually this course period is of 6 weeks but I completed the whole course within a week because of the tutors .

교육 기관: Peter G

Feb 26, 2016

Very nice brief introduction into the field. Gives good overview of main concepts: 1) statements of problems in machine learning 2) approaches to finding solutions 3) methods to evaluate resulting solution . Systematic material presentation with good examples and analogies.

교육 기관: Zachary N

Dec 13, 2015

Great overview of machine learning techniques and practices at a high level! There is sufficient material here to go from no machine learning knowledge (and a general programming background) to being able to create and deploy machine learning models for use in applications.

교육 기관: Aman A

May 26, 2016

Awesome way of teaching that too from a well qualified faculty. Rather than imparting theoretical knowledge, great focus is on practical knowledge that's what I like about this Course. Thanks to Coursera for giving me this opportunity to get tutelage from such an erudite.

교육 기관: Mayuresh W

Nov 23, 2015

The course was well detailed and gave a good idea of what to expect when learning about machine learning and this specialization.

Covering each of the topics well with sufficient explanation and a small project was a great way to learn.

Looking forward to the next courses :)

교육 기관: Gerard Y

Jul 27, 2018

Very good overview, the lectures were enjoyable to follow, and brought good intuition on the topics with a good sense of what was possible. The exercises were of reasonable difficulty, and not too hard to set up, allowed to get a good feel of the potential of Turi Create.

교육 기관: gaoyu_xinghuo

Jun 20, 2016

Exclude the last part, the whole session gave us the clear picture about machine learning -- What the machine learning is , how machine learning works and how to use machine learning to change the world:)

I love the course, it gave me a lot. Thanks Emily and Carlos again.

교육 기관: Daniel R

Feb 07, 2016

It is a really well thought introduction for Machine Learning. It is almost unbelieveable that you could use every single technique in less than a month. Of course using a framework, but if you are really interested you could do them with open source tools.

It is amazing!

교육 기관: Arjun P

Mar 24, 2020

A very good course that gave me a jump start to machine learning application and got me right into coding the applications. This course takes a very different approach to teaching ML and I guess it works as it keeps me interested and makes me want more from this course.

교육 기관: alexandre l f

Oct 22, 2017

Case study base approach makes this course pragmatical and business oriented. A great team with good tools and exercise which deserves a 5.

Note : math's background is low (or more exactly far from the target of this course) and might be a blocking point at some stage.

교육 기관: Raphael K

Feb 29, 2016

Nice class, give a brief introduction to all the methods use in ML without going deep. If you just want to get an idea of what ML Technics are and how to implement them this course is for you. If you are want more technical details about ML this class is not for you.

교육 기관: Yaobang C

Aug 29, 2018

I am very grateful to the coursera platform for giving me the opportunity to learn, and I would also like to thank the two professors for their careful preparation of the wonderful lectures. I learned about machine learning and fell in love with ipynb, thanks again!

교육 기관: Jose N N P

Mar 30, 2018

Excellent course and very challenging, most importantly, I have learned a lot and I have a great understanding of what machine learning is. Dr. Carlos and Emily are great instructors, and indeed engaging as well as passionate. Looking forward to taking the next one.

교육 기관: Easton L

Feb 25, 2017

Emily and Carlos are really exciting teachers. This course covers fundamental concepts of Machine Learning and comes with very practical assignments. I've learned a lot from the this course and I believe it will make me ready for more challenging work in the future.

교육 기관: Alan B

May 15, 2020

Material was presented in a practical way, making it useful to relate the theoretical concepts to real life applications.

One suggestion might be to speed up the video while typing comments and mistakes while typing, etc. just to make the experience more enjoyable.

교육 기관: Martin K

Mar 26, 2016

First of all I want to thank you for conducting this course. I have learned a lot from the course. This course gave me basics understanding of machine learning. You did a good job presenting complex machine learning algorithms in a way that everyone can understand.

교육 기관: Donald M

Dec 14, 2015

I have loved this course. The approach to learning is most fruitful as I have learned a great deal and had a lot of fun along the way. I am on the last exercise to finish the class after about 4 days. I am going to savor this last one because this was too much fun.

교육 기관: Anatoly M

Apr 16, 2017

Great introduction to machine learning, not too much math but gives a good idea of what ML is + gives practice in Python (which was my initial goal).

The tests contained a few inaccuracies (they didn't completely match on my machine/setup), but otherwise was fine.

교육 기관: Ravindra P

May 26, 2020

Great Course to start with machine learning. When I started this course I heard bad words about turicreate. But I think it is very easy to work with this compare to pandas. And it will even save your time that you can invest in learning more theoretical aspects.

교육 기관: Vinay S

Jun 01, 2016

Very interesting and fun course for really complicated topic. The best part of the course is the recommended software tools they are brilliant designed especially graphlab.create. Both the instructors are really engaging and teach complicated topics really well.

교육 기관: Ravindra M

Dec 09, 2015

Case study approach works !

I completed this course and found course materials present intuitive. Following courses go deep in each method.

Thank you Emily and Carlos :-)

A small request to Coursera to provide course completion certificate to free account like Edx.