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Bewertung und Feedback des Lernenden für Machine Learning Foundations: A Case Study Approach von University of Washington

12,871 Bewertungen
3,065 Bewertungen

Über den Kurs

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....


16. Okt. 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

18. Aug. 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.

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526 - 550 von 2,990 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Uday A

14. Juni 2017

A perfect introduction to ML. Couldn't ask for more. 6 weeks of coverage is neither shallow nor too deep. Sets up the stage nicely for a deeper dive in next sessions.

von Vaibhav O

25. Dez. 2016

Great course to begin your journey into ML

Briefly introduces each topic to give a jist about it and also provides a good starting point for using python in ML context

von Angel G C

13. Dez. 2015

In a couple of Case Studies it gives you a wide idea about the almost unlimited potential of Machine Learning while it encourages you to learn more and more about it.

von CO17 3 G

7. Juli 2020

it was really amazing to learn from these mentors. They were really humble, clear and had an interesting way to teach. I would love to attend more of them in future.

von Deleted A

18. Sep. 2018

This course gives a really easy but clear concept for machine learning with examples! I hope I can learn something further with other courses in this specialization.

von William C

22. Okt. 2017

Fantastic course, great 'learn-by-doing' introduction to ML, really entertaining teachers kept me alert throughout each session. It was great fun and I learnt a ton!

von Sergio B S M

12. Juli 2020

The course is very well structured, interesting lectures with real-life applications, and the programming examples and assignments were very useful and instructive.

von Stefan v D

4. Feb. 2020

A great foundational introduction to Machine learning concepts. Ideal for people that have some background in maths and programming but no career in this direction.

von Prashant S

19. Okt. 2018

This is a brilliant stepping stone for Machine Learning world. Basics are being discussed and explained in a very simple manner. thanks to the teachers and Coursera

von Shital M

20. Nov. 2017

Fantastic overview of various machine learning methods. Very interesting way of exposing concepts using case study approach which makes it more engaging and useful.

von Fernando M P

10. Aug. 2017

This course is a wonderfull introduction to the Machine Learning. It provides a good start point which is very helpful with the other courses of the specialization.

von Fabricio N

27. März 2016

Best course in data science out there. Believe me, I did all 4 other Specialization, some of then very good, some of then no quite si, but this one is far the best.

von Chris H

24. Dez. 2015

A great introduction. Good relevant examples and thoughtful data sets were provided for the exercises. Both lecturers were engaging and clearly knew their subjects.

von Muhammad M

21. Juli 2020

The course is easy and good for beginners. Specifically, case study approach is quite good and furthermore hands on practice assignments greatly improves learning.

von Sumit

8. Juli 2016

Excellent course, gives good overview of all the different ML algorithms.

Case studies and assignments are really good and help a lot in understanding the concepts.

von Ali A

21. März 2016

This course builds a quick but engaging overview of machine learning. The structure is more than amazing, the style of teaching is very narrative and very helpful.

von Liliana R

22. Jan. 2016

It is a great course to learn the fundamentals of Machine Learning, also Emily and Carlos are excellent tutors, they explain very well and they give good examples.

von Vinícius N d O

6. Okt. 2020

Good course. Strongly application-oriented, intermediate level but with some basic points as well. I think the course could improve a bit on the theoretical side.

von Gyrdymov I

12. Nov. 2017

Amazing course. It has given me good base knowledge of ML algorithms, I consider the course a "map" for further exploration of Machine Learning world. Good start!

von Marcus V M d S

1. Okt. 2017

Thank you very much for this course! I really appreciate the effort put into the notebooks and the preparing of the data, and the graphlab library is really cool.

von Guo X

10. Aug. 2017

the course is great. I love case study approach for the machine learning foundation. I really love to go on learning in the following parts of the specialization.

von Ricardo J F

17. Sep. 2016

I believe it would be very useful if the authors could provide a lecture review about python commands. Specially the ones they are going to use during the course.

von Christopher G

25. Jan. 2016

Excellent, practical introduction to the topic -- particularly by using use cases that everyone can relate to in order to understand how machine learning "works".

von Hui Z

4. Mai 2020

Carlos and Emily provide excellent lectures. But it would be better if correct answers and detailed explanation can be provided for each assignment in the course

von Adarsh K

10. Apr. 2020

course and the instructors were very good.

But figuring out how to install all the softwares in windows using wsl and copying files into that was a little tricky.