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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
12,660개의 평가
3,030개의 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 2,949개 리뷰 중 201~225

교육 기관: Abdallah G

2017년 1월 18일

This course was really good I found it a really good start I also really like the way in which Emily was giving the theoretical parts then Carlos follow her with the practical part . Also Emil and Carlos have a really Excellent way in explaining the course material which make it really entertaining .

Thank you so much I really loved and Appreciated every part of the course.

교육 기관: Pratyush D

2015년 10월 6일

I have been halfway through the course and it is excellent if you want to build strong foundations in Machine Learning. A basic level of experience in programming is required. Python is the medium in which programming assignments have to be done. But if you have a certain level of proficiency in any language then you won't have any problem. Anyways, great going till now.

교육 기관: vinit s a

2016년 11월 23일

Amazing course. I would recommend this course to get started on machine learning and understand its applications. This course doesnt go deep into the complex mathematical theory unlike others and the instructors do a very good job in going through the material systematically. Assignments are a bit challenging but manageable since graphlab has a lot of inbuilt libraries.

교육 기관: Udhay

2015년 12월 8일

Excellent course to start the ML concepts ! The Case Study approach really gives a deep insight into each concept discussed. Looking forward to further courses in this specialization !! My python programming knowledge really helped to complete the course few weeks earlier !! Suggestions : An example using the python ML modules -sclearn,numpy,matplotlib will also help !

교육 기관: Julius L W

2021년 5월 13일

I really recommend this course, it consist of easy-to-understand theory and the hand-on also very easy to follow. Having basic to intermediate level of python really helped you to progress this far, and if you always use Pandas, Turicreate and SFrame data manipulation could be a new learning curve for you, but again everything is google-able. Thanks for this course!

교육 기관: Sruti R

2018년 2월 21일

If you are looking for a course to find out what machine learning is. This is a great course. I only completed the first course so far and It has given me a basic understanding of what machine learning is about, the basic techniques, introduction to software used for machine learning and a look at what's ahead to deepen the learning if I choose to pursue this line.

교육 기관: Theodore G

2016년 10월 23일

A really interesting, introductory course in Machine Learning Methods and their applications. The case study approach followed by the instructors makes it ideal to learn how these ideas used in real-life problems. The programming language used is Python (GraphLab Create or Open Sourced libraries), which is most probably the best choice for newcomers in the field.

교육 기관: Fabio P

2016년 3월 25일

After going on with the specialization I started to understand how great this first course really was: It teaches you lots of basics while not expecting too much and shows how you can use machine learning in different scenarios.

On it's own it's possibly only worth 3 stars, but in the context of the whole specialization and further courses it's definitely 5 stars!

교육 기관: Paul P

2017년 3월 7일

This course is great for anyone who wants to not only get a great overview of the concepts of machine learning but apply the concepts and see the results in week 1! You'll be using machine learning algorithms to train models with real data even if you have no idea what that means! If you're taking the time to read this review you should probably take the course!

교육 기관: Matthew B

2016년 6월 4일

This is a great class! Highly recommended. Emily and Carlos are a great team. The videos are polished, the progression through the material is well organized and everything just fits together very well in this specialization. The assignments are challenging enough to be worth the effort. Great specialization... I look forward to completing every class.

교육 기관: Stefan K

2015년 12월 28일

Very good introduction to machine learning, the teachers and assignments are very well planned and executed. It is a course where you can spend more time, as the workload is bigger than at usual courses, but you learn a lot every week. I am really fan of this Specialization and I plan to complete the whole Specialization given enough time in near future.

교육 기관: YASEEN S Z

2017년 10월 7일

You were very near to be the legend of Machine Learning but after cancelling the capstone project you aren't. I'm really disappointed, why great things always not completing. I wish you to provide us with at least IPYNB for the capstone project because that will help us a lot. Finally, this is a really amazing course. Thank you for this great course.

교육 기관: 이제민

2015년 12월 13일

that's awesome course. They bridged between theorem and practice. so we can imagine and know how to apply machine learning algorithm in real world and real problem. what's more, we can adjust and tuning machine learning algorithm to make customized algorithm. I am very confidence this course should give everyone great opportunities and good insight.

교육 기관: Suchismita R

2019년 9월 14일

Machine Learning Foundations manages to provide a very intuitive impact on the understanding of the need and the accuracy of various ML techniques. The course takes the participant through a thorough conceptual and program-based approach. The various Algorithms and concepts are explained in utmost details, and the exercises are fun and challenging.

교육 기관: AMS - o

2019년 7월 22일

Aside from few technical difficulties, a very well designed and thorough course - this case-study approach is obviously a lot more involving and relatable than just dragging one through a bunch of theoretical concepts and equations (not that the latter is inherently bad, the other one is just more fun :). Would recommend to anyone interested in ML.

교육 기관: Omar S

2016년 8월 22일

A Brilliant introduction to Machine Learning, I've tried several courses before but none of them got me engaged like this one. The instructors have a lot of knowledge and present the material in a very easy to understand way. Also the assignments and technical work is really engaging and challenges you to really learn the language and the concepts.

교육 기관: A. B

2016년 2월 29일

Great course--I love the case study approach! Combined with both instructors enthusiasm for the subject, the approach was a great way to ground the theory. The quizzes & labs guided a deeper exploration into the topics the details presented in the modules.

I'm excited to continue digging into the course material while moving towards the capstone.

교육 기관: Daniyar M

2016년 2월 17일

I thoroughly enjoyed the course. I was hearing about Machine Learning so much that i decided to see whats the big buzz about, and big it was! Now i have some of the ideas for my own projects and some solutions for old problems. And must i say that the instructors are amazing, really love their job! Will definitely use graphlab in my work from now.

교육 기관: Teo J

2020년 5월 8일

First of all, I want to say that the interactions between the two professors was, in the most academically professional way, adorable. They clearly know and love their material, and are clearly relaxed and enjoying teaching. It was easy to learn from them, the lessons were well-scaffolded, and I only wish I could take courses like this on campus.

교육 기관: Sabarish V

2018년 4월 18일

The course is easy to follow. With the IPython notebooks that are already filled in complementing the teaching, everyone can appreciate the applications of machine learning. What's even better is that, because of the notebooks, one can see that one doesn't necessarily need to be very skilled at maths or coding to build their own application.

교육 기관: Hans G Q

2020년 10월 11일

An amazing course! If you don't have any idea of what is Machine Learning, you will find this course very helpfull. You will walk through different mathemathical concepts as well, but with some research you will doing well!. Excellent for have a big picture of what's going on with Machine Learning and see practical examples on how it works!

교육 기관: v s

2018년 3월 24일

this is pretty cool, I enjoy this course and the dynamic between the instructors. This course touched on important concepts and purposely omitted the details of the underlying math and algorithm in order to give you a bird-eye-view of the ML landscape. It also wets my appetite to learn more about the details behind the magic! Good approach.

교육 기관: Alan L

2017년 12월 21일

Amazing Introduction to ML. I came in with little understanding of ML and no Python or coding experience. I had to do most weeks twice while learning extra Python on the side from Code Academy but if a complete novice like me can do this anyone can! The professors are great- they're great at breaking down complex ideas into simple examples.

교육 기관: Bruno L

2016년 12월 19일

In this course, you use ML algorithms that are already implemented to solve various kinds of problems. The goal is to give you a broad overview of ML and how it can be used to solve real life problems.

Subsequent courses of this specialization dive deeper in each algorithm. You'll learn the theory behind them and implement them from scratch.

교육 기관: Pravin J

2021년 6월 14일

Great course for folks who have not been exposed to all the concepts of ML, the video lengths help you pick up from where you left off for working professionals, the assignments and quizzes and intuitive and not overwhelming. Also love the case study approach where the problem statement is first presented and how the solutions are achieved