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

13,205 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....



19. Dez. 2016

Great course!

Emily 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.


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

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501 - 525 von 3,063 Bewertungen für Machine Learning Foundations: A Case Study Approach

von 向韵桦

31. Jan. 2016

It's really helpful to pull back and have a overall look at these algorithms. Especially, the professors gave a very clear talk and explanation which made this course more impressive.

von rambarki g

11. März 2018

This was a awesome moment for me it was really cool. The people of course era i love them .Thank you so much for financial aid. Keep supporting people like thank you thanks a lot!!!!

von Wenxin X

25. Feb. 2016

In my opinion, the course is well designed. I generate a rough idea about the basic concepts of machine learning through it. These concepts are important but made easy to understand.

von Jerome G

28. Dez. 2015

Excellent overview of machine learning technique !

Even if the subject is complexe, it's easy to understand, and a good starting point to go deeper, as a deep human learning can be ;)

von Udaibir S B

11. Mai 2020

The course was up to the mark, the quality of the assignments and quiz was also good which created the course more interesting to learn and learned many new things with this course.

von MOON E H

8. Jan. 2018

1. the lecture was very useful for me. it is helpful for me in my working field

2.i would recommend this lecture to my companies

3.I could understand Artificial Intelligent concepts

von Corey H

14. Aug. 2016

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.

von Juarez A

22. Feb. 2016

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!

von Kevin Y

11. Jan. 2016

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.

von Aimeeking

21. Dez. 2015

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

von Aruna H

16. März 2016

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.

von Vivek V

13. Dez. 2015

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.

von Neelam G

26. Juli 2020

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.


1. Juni 2020

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.

von Rohan C

19. Juli 2018

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.

von Stavros

4. Dez. 2016

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.

von Rohan K A

20. März 2016

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

von Ben J

25. Nov. 2015

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.

von Shawon P

16. Mai 2021

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.

von Muhammad A

5. Nov. 2018

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.

von Pooja G

7. Aug. 2018

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.

von Remy d R

6. Mai 2016

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).

von Cristhian C C

23. Juni 2020

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

von Francisco P

25. Juni 2017

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!


1. Sep. 2020

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.