Chevron Left
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
13,053개의 평가
3,105개의 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

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.

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

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 3,032개 리뷰 중 476~500

교육 기관: Corey H

2016년 8월 14일

This course is light because it is a survey--a taste--of what the rest will offer. Nonetheless, it sets up a starting point for future classes. The instructors are genial and fun.

교육 기관: Juarez A

2016년 2월 22일

Great material to get you started with machine learning. Covers a bit of different ideas used in machine learning. It definitely got me eager to learn more in the following courses!

교육 기관: Kevin Y

2016년 1월 11일

This course is awesome. Nice concise videos, great assignments and quizzes to follow along.

It's very practical so you come out of it with a bunch of tools you can use straight away.

교육 기관: Aimeeking

2015년 12월 21일

This is my first time to Study inCoursera.Mrs Fox and Mr Guestrin are so outgoing.its really a good oppotunity to take me into a new world.It is really wonderful introductory course

교육 기관: Aruna H

2016년 3월 16일

Really like the case study approach. IPython notebook and graphlab are amazing tools. I am in week 4 now and was never bored. Hope the upcoming courses will be as good as this one.

교육 기관: Vivek V

2015년 12월 13일

Love the practical application and the high level over view of the varius machine learning techniques. I would say this is an excellent course for introduction to Machine Learning.

교육 기관: Neelam G

2020년 7월 26일

Excellent experience of learning though faced a lot of issues in the installation of required softwares. Thank you so much Emily and Carlos for such a lively delivery of lectures.

교육 기관: VAIBHAV D

2020년 6월 1일

This course is very help full who can start machine Learning because the understanding and explanation is very clear and i am so exited to get other course in this specialization.

교육 기관: Rohan C

2018년 7월 19일

Emily and Carlos made this course really enjoyable. The Case Study approach really helped with better understanding of many concepts. I highly recommend this course for beginners.

교육 기관: Stavros

2016년 12월 4일

It's a very good and very structured course which gives you a very nice insight of all the basic concepts in machine learning today and prepares you for the next courses to come.

교육 기관: Rohan K A

2016년 3월 20일

It is a great start towards the world of Machine Learning, very nice experience to study concepts based on different case studies. assignments are also challenging and interesting

교육 기관: Ben J

2015년 11월 25일

I really enjoyed the course. I found all of the problem sets to be useful to reinforce what was explained in the course without being extremely difficult to get working correctly.

교육 기관: Shawon P

2021년 5월 16일

This is the best course i found on machine learning so far available online which takes strong knowledge in Python and good understandings of mathematics. I loved it by my heart.

교육 기관: Muhammad A

2018년 11월 5일

This course is very much helpful for me to get understanding about python, deep learning, neural networks and the things like this. Thank you so much for help and guide me a lot.

교육 기관: Pooja G

2018년 8월 7일

Loved the course content. Particularly loved the usage of iPython notebook. very relevant & useful. Special thanks to the course instructors for helping guide through the course.

교육 기관: Remy d R

2016년 5월 6일

Excellent course, highly recommended. Hands-on and really easy to follow. Would love some more background / reading about the applied statistics though (since this is new to me).

교육 기관: Cristhian C C

2020년 6월 23일

Very good course on the fundamentals of Machine Learning. It introduces introductory and practical regression analysis, classification, recommendation systems and deep learning.

교육 기관: Francisco P

2017년 6월 25일

Thanks to the teachers, they prepared exciting, complete and interesting clases. The course is very useful to understand the main areas in machine learning. Totally recommended!

교육 기관: JONATHAN F G H

2020년 9월 1일

The use of case studies helps a lot to understand the concepts easily. The teachers' presentations were very funny and clear to understand the concepts presented in the course.

교육 기관: Nikhil R

2019년 7월 11일

Really a great course for getting started in machine learning, it helped me a lot for learning the fundamentals before jumping to the more complex parts in the Machine learning

교육 기관: Daniel T

2016년 10월 9일

A fantastic course! The case study approach really makes a difference. I can't stand purely theoretical courses so this one really stands out. Best ML course online hands down.

교육 기관: Steven G L

2015년 10월 28일

This is a great course that presented a review of the introductory concepts of Machine Learning, furthermore the implementation of the techniques are simple and easy to deploy

교육 기관: Matt M

2015년 10월 19일

I have worked through a number of machine learning courses, and this is by far the best. The course materials and the ipython notebook walk-throughs are incredibly informative.

교육 기관: Sivakumar R

2018년 9월 18일

Very practical and use case based method allows to understand concepts. Hands on training brings confidence to non-software student like me. Thank you for the valuable course.

교육 기관: Nand B P

2017년 6월 27일

Best Introductory course for Machine Learning for beginners as it shows an abstract yet hands-on type of approach to cover all the important topics related to the ML concepts.