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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
9,038개의 평가
2,159개의 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.

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.

필터링 기준:

Machine Learning Foundations: A Case Study Approach의 2,078개 리뷰 중 101~125

교육 기관: Chao L

Mar 04, 2019

It is good class for people want to ML and start from scratch

교육 기관: Lahiru H P

Mar 04, 2019

great course content to get started with machine learning and also for deep learning.

교육 기관: Mohit C

Mar 05, 2019

The idea on the teaching method by taking case study was a great choice. Great work keep it up.

교육 기관: Almir I

Mar 05, 2019

Great course. Very clear and detailed presentation of concepts and techniques of Machine Learning.

교육 기관: Aries F

Mar 06, 2019

Very easy to understand, code are very simple and to the point

교육 기관: Akash G

Mar 08, 2019

START basic like star

교육 기관: Muhammad A N

Dec 06, 2018

Excellent

교육 기관: Rania B

Jan 06, 2019

I had to use TuriCreate instead of GraphLab, so other than the changes in the libraries that had me guessing which function to use, everything in this course is well structured and concrete. Thank you all!

교육 기관: Christopher M

Dec 07, 2018

This was a great course. The instructors were fun and knowledgeable and the assignments were well-written. I loved the flexibility of being allowed to use whatever software I wanted to solve the ML assignments since the quizzes were based on the results of the modeling rather than submitted code. For some assignments I used sklearn and for others I used the software recommended by the instructors (graphlab).

교육 기관: Divyansh S

Dec 25, 2018

I found this course advantageous for me. I found the case study approach of teaching the various concepts of Machine Learning quite helpful. Case Study approach gives us the idea of practical implementaton of these concepts in real life. The quality of the teaching content was very good. Moreover the assignments helped a lot in understanding some of the key concepts. Ideal course for newbies to start learning Machine Learning.

교육 기관: Artem

Jan 08, 2019

awesome course with theoretical and practical knowledge

교육 기관: Wilfrid L

Jan 08, 2019

Very good course, I enjoyed the way the instructors structured and presented the material, in both a professional and personable manner, and the use of case studies to help solidify the knowledge. Assignments were very well built; although they used quizzes, it really required some thinking and prep work to get the answers right.

교육 기관: Sameh

Jan 20, 2019

very good and very nice course, it added lots to me

교육 기관: Genyu Z

Jan 20, 2019

This course is very useful. Firstly, it helps me to build a perfect python environment. Secondly, it teaches me how to use jupyter notebook correctly. Teachers are very kind, and I like their teaching ways. If I can build algorithm without graphlab, it will be more challenging.

교육 기관: Walt M

Feb 04, 2019

create videos and hands on practices

Neural network part should be enhanced with more common frameworks, such as TensorFlow/Keras

교육 기관: Rohan V

Feb 13, 2019

this has been one of the best courses that I have taken online and the output from this is seriously amazing. It really makes your brain work and the forums make sure you don't get lost. I am definitely going to do the specialization course

교육 기관: Evan S

Mar 11, 2019

This course was a great balance between lecture (and lecture quiz) & iPython lecture (and iPython lecture quiz). I like that the answers are multiple choice as opposed to copying and pasting code. That way, any coding errors can be played around with in the notebook first without using up any submission attempts. Emily and Carlos did a great job of keeping the course fun while sticking to the easy-to-understand case-study approach.

교육 기관: Le N P

Jul 16, 2018

thanks instructorsthis is a great course for learning ML

교육 기관: Sai K

Jul 10, 2018

Very good learning experience. Provides a basis to understand the various models for various scenarios.

교육 기관: Arun K P

Jul 10, 2018

Very good concept, It opens the

교육 기관: XIAO N

Jul 13, 2018

I like the approach and this is a relatively easy module

교육 기관: Bhisham J M

Sep 22, 2018

I found course content and they way it is designed is perfect for anyone to easily grasp the concepts. I am from non-development background and don't have much grip on python language but it was still smooth and easy for me to progress this course by learning python basics and commands as well which is required for programming assignments. Well done coursera, keep up the good job!

교육 기관: Nagendra K M R

Sep 22, 2018

Explanations are provided in detail which helps even the beginners to master the Machine Learning. Case studies are very interestinghelpful to master the concepts and gain the confidence.

교육 기관: Magdi M

Sep 11, 2018

Great case coverage

교육 기관: Rahul K

Sep 11, 2018

The lecturer's teaching is well organized and presented, which helped me to accept the new knowledge quickly.