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

13,055 Bewertungen
3,105 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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2901 - 2925 von 3,034 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Konstantinos L

8. Jan. 2018

Nice course but too easy. Assignments should be more difficult

von Seong H M

25. Sep. 2021

Problems and files and videos not updated base on the changes

von Felipe A S S

23. Jan. 2021

The libraries used on the course are a little bit unsopported

von Nadeem B

27. Juli 2021

Concepts and explanation is great but using outdated modules

von Atharv J

14. Sep. 2020

The course should be taught in pandas rather than graphlab.

von Max F

10. Jan. 2016

Not a bad course, but extremely basic. Was expecting more.

von Adrien L

2. Feb. 2017

No good without the missing course and capstone projects

von Aleksey C

11. Dez. 2016

....mmm fsdfg gsgsd sgsdgsdg sdsdgsdg ggsgsd sgdsdgsg


15. Juni 2020

Installing software parts gave me a very hard time.

von Bastian M P

1. Juni 2016

Could go a little more in detail on the algorithms.

von Jaime O

31. Jan. 2017

The Deep Learning part needs to be improved

von Chen S

26. Okt. 2015

Very basic, the quizzes aren't clear enough

von Li-Pu C

29. Okt. 2020

A little bit too easy, but good for rookie

von Harsh V K

8. Mai 2019

Should use Python 3 instead of Python 2

von Phú L L H

3. Apr. 2021

sofware guideline is quiet useless

von Yu G

7. Feb. 2021

No idea what to write here...

von Jorge C

29. Mai 2016

It is a very simple course.

von Ricardo S

10. Aug. 2021

Feels a bit out dated


25. Juni 2020

Good for knowledge

von Fredick A S

6. Apr. 2018

No python..

von Nasimul J F

16. Aug. 2020


von Kai C

24. Nov. 2015

Too easy

von Geetha G

16. Aug. 2021


von Anshu R

12. Sep. 2020


von sakthivel

4. Sep. 2020