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

12,854 Bewertungen
3,062 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....


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.

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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426 - 450 von 2,984 Bewertungen für Machine Learning Foundations: A Case Study Approach


28. Sep. 2021

very nice course.If you have basic knowledge of python datastructure then this course is best to start data science.All contents are beginner friendly which makes this course easily understandable.


11. Feb. 2019

The course module is very clear and very useful for me to understand the ML concepts.

Really excited about more features in the C_Stone project where i think we can do something for my organisation.

von Rebekah H

9. Juni 2017

I felt this course did a good job introducing the student to Machine Learning. The examples and hands on assignments brought the concepts home. I was able to use the knowledge immediately at work.

von Govindarajan

4. Juni 2017

This course is very helpful for people who are novice in machine learning. The course uses Graphlab Create which is different from scikit or R-libraries, but the tool(Graphlab) is excellent to use.

von Bhavesh G

28. März 2020

This course foundation for those who want to do specialization in Machine Learning. It's really very useful course, I recommend do this course If you want to do specialization in Machine Learning.

von geetika s

8. Nov. 2016

One of the best courses available online. Actually got to know how to apply theoretical knowledge in designing systems. You people are the best and made concepts and things really easy. Hats off!!

von Ashley A

14. Nov. 2016

Really liked the course and the teachers. Would have preferred more detail on the quizzes so I didn't feel as lost as I did some of the times while trying to piece together what a question meant.

von Chandrabhan

21. Juni 2020

I'm very thankful to coursera. It's provide a cost of free certification of machine learning which cost in market is approximately 3000rs.i think coursera is a good platform. Thank you coursera.

von Sarim A

7. Okt. 2017

really like the instructor and the course. it was very hands on specially for me who is coming from Bigdata (python and hadoop) background . thanks for this cool and amazing learning opportunity

von Amr H

20. Juni 2018

The course Content is very good and also the instructors .graphLab tool is also good toolI wish there was a hint for scikitlearn but it is a good course for beginners and i Recommend it for all

von Jesse C

28. Aug. 2021

R​eally enjoyed all the material presented by the professors! They're enthusiasm for machine learning is contagious. I would highly recommend this course as an entry-point to machine-learning.

von Naveen T

24. Apr. 2016

Excellent course! I like Emily and Carlos' approach to delivering online courses and the content and structure of this specialisation. I would definitely recommend this course to my friends.

von Joseph K

29. Okt. 2015

Great survey course for main topics in machine learning without going too much into detail. The professors do a great job of keeping the topics relevant to modern-day uses of machine learning.

von Nasir M

12. Aug. 2020

Excellent foundation course on ML, Enhanced the wish to learn detailed topics in ML, very attractive methods by Instructors, Thanks for creating thirst and encourageuing to learn more on ML

von Aradhika N

21. Juni 2017

Love how the modules are broken down into small segments of 3-5 minutes on an average. Makes it easier and definitely not monotonous as compare to other courses. The professors are amazing!

von Mahmoud A E

28. Feb. 2016

The top-down approach of this course is the best way to understand concepts and view solutions for real-world applications. This way I can go deeper after understanding why I am doing this.

von Nagendra K M R

22. Sep. 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.

von Robert R

25. März 2018

A running Jupyter notebook with working examples. Very nice. I couldn't get my local system setup the way they explained, probably because my Python is 3.x is newer than 2.x. Not sure.

von Dauren

22. Dez. 2017

Gives a good overview of tools and models used in Machine Learning. Once taken this course, you will have a general knowledge of domain upon which Machine Learning methods can be applied.

von Ramy S

22. Juni 2019

Excellent course. I am currently working at and find that this is a perfect supplementary course that will allow a professional to solve business problems. I highly recommend.

von Joseph L

28. Feb. 2016

Had a blast. I have no background in ML whatsoever. But the tools, concepts and exercises presented is really interesting and really help set the mood for the rest of the specialization.

von Rogelio Z R

3. Dez. 2015

Emily and Carlos are amazing! The course is well laid out, specially as part of the specialization, taking the regression course would have been different without the foundations course.

von Francesco P

16. März 2021

Nice introduction to DL, easy to follow with the suggested turicreate or any other framework.

IT is juts a pity that the specialisation this course belong to will no longer be completed.

von Prabuddha K

2. Apr. 2017

Brilliant overview. Many thanks to the teachers for designing such a comprehensive overview. This course must be followed by all the others in the specialization for best understanding.

von Richard K

16. Dez. 2016

Great course, really well designed and with some interesting real life case studies. Lectures are clear and informative and the assignments help cement your understanding of the content