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

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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....

Top-Bewertungen

BL
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

PM
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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501 - 525 von 2,990 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Marcus C

8. Feb. 2016

great course. This covers all types of machine learning techniques deep enough to get a basic idea how things work. Enjoyed a lot. Instructors are really fun to learn from.

von Cissy S

2. Dez. 2015

Loving it so far! Can't wait for the other courses. The case study approach is spot on! This is the first coursera course that is worth something! Kudos to the instructors.

von Pankaj K

25. Sep. 2017

Nice overview to ease into all the content!, Only bad this is they use sframe :( either make it opensource and in the mainstream use or provide the assignments in sklearn!

von SMRUTI R D

15. Feb. 2016

A very informative beginners cource which offers a macro view of different approaches to MachineLearning and prepaes the student for further study in each different areas.

von Kirill L

3. Feb. 2016

Great for a start.

Still has some issues for those who use sklearn and pandas.

Also I'd prefer to see more detailed info on neural networks instead of deep learning module.

von Fabian d A G

15. Aug. 2021

E​xcellent course that spans the broad ML domain. Unfortunately it appears that the specialization ends sooner than what was planned, but remains quite good nevertheless.

von Vishal A

29. Nov. 2017

They have used graphlab instead of using standard library. But overall good course.

If the student can submit quiz question without enrolling then it would be a big plus.

von Amy M

11. Juli 2017

The instructors were fantastic, the material was understandable, and the reach I have beyond this course is still expanding. Thank you for a wonderful learning experience

von Dan S

13. März 2016

I found this course as a great introduction to the world of machine learning with a very practical approach.

I'm waiting forward to the next courses in the specialization.

von Thomas K

5. März 2016

I loved this course! It is really well done, that you have a theory part and a practical "case study" part, were you can follow along with the provided IPython Notebooks.

von Eric A J C

17. Apr. 2021

An excellent course to get introduced to the field of Machine Learning. Amazing professors! And actually putting the knowledge into practice with Python was a big bonus.

von NITISH C

10. Sep. 2019

This course is designed in a very planned way. It gives you a bird's eye view of the ML world without boggling down you with too much technicalities. Highly recommended.

von Muhammad U C

11. Feb. 2016

A good theory and practical based overview of major machine learning tasks. Hands-on practice using GraphLab Create makes it one of the best courses in Machine Learning.

von Sanath K S

5. Aug. 2020

An immaculate course to get your basics and facts right to get a head start in ML.The mentors did their part well. I strongly recommend the vert course to the aspirants

von Deveer B

22. Dez. 2019

Very good theory and practical approach. However, some of the assignments are not very clear while explaining the questions due to which sometimes we get wrong results.

von Mohamed A H

23. Okt. 2018

The instructors are very professional, straight-to-the-point, and they have a nice sense of humor :)

which made the course much more interesting. Definitely recommended!

von Mykola D

9. Juni 2018

I really like this course. I've learned basics of ML. I've really enjoyed the presentation style. The practical part was great. I am looking forward to the next course.

von Franklin F

16. März 2018

Clear and fun instruction. The course gave relevant and tangible examples of machine learning in practice and the coding was very managable for a non-systems engineer.

von Yeremy T

15. Feb. 2016

Great introduction to Machine Learning and the different ML methods. Assignments were not mean to be hard, but practical, which I appreciate. Great instructors as well!

von Jagdish B P

20. Juli 2019

This is a fantastic course. The concepts are explained so well and are followed by hands-on which helps a lot. Case Study approach really is working well in this case.

von Dennis S

28. Apr. 2017

Great presentation of the topic and fitting complexity / depth for an introduction.

Way better then all the other courses i tried before. Great instructors and concept!

von Zeph G

1. Jan. 2016

This is a nice introduction to the concepts that will be covered in the specialization and the power of the provided GraphLab Create ML toolbox. I highly recommend it.

von Gwendolyn G

24. Nov. 2015

This is a really good intro course. It's not pitched at a terribly high level of difficult, but it does give you a fair amount of practice. I'm really pleased with it.

von Satish K D

25. Nov. 2018

Very informative in basics of Machine Learning. It sets the stage for a deep dive into the topics of machine learning like Regression, Classification, Clustering etc.

von Chengran Y

2. März 2018

This course is really useful, as a overview of the whole specialization. The quiz for theory and python implementation strengthen the key points for each module/week.