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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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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

SZ

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.

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

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2776 - 2800 von 3,071 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Binil K

•

10. Jan. 2016

Really great one!!

von Hiếu N Q

•

28. Dez. 2015

Good for ML newbie

von amit d

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3. Feb. 2020

nice explaination

von Arnab N

•

5. Jan. 2020

Very nice program

von Rahul S

•

19. Dez. 2020

GREAT EXPERIANCE

von SURUTHI T

•

5. Juli 2020

more informative

von Oscar M

•

29. Mai 2016

Very insightfull

von Tulasi P D

•

15. Juli 2020

it is so useful

von Rohit K

•

17. Apr. 2020

very intersting

von shane

•

22. Okt. 2015

Very practical.

von Rohit K S

•

30. Sep. 2020

Good Course!!

von Divyashree

•

14. Sep. 2020

A good course

von SHAHID S

•

16. Mai 2022

Nice Content

von ANURAG Y

•

30. Nov. 2021

good teacher

von Rupali G

•

2. Nov. 2017

good content

von Andre G

•

14. Mai 2016

Good course.

von 廖敏宏

•

24. Sep. 2020

Very useful

von P.BHUVANASHREE

•

18. Sep. 2020

interesting

von HASNA V N

•

19. Juli 2020

Good course

von Shubham D

•

3. Dez. 2016

nice course

von Le H P

•

16. Aug. 2019

well done!

von Daniel Ø

•

18. Jan. 2016

very basic

von Muhammad A K

•

27. Nov. 2020

very good

von Sayam N

•

25. Sep. 2020

Excellent

von Aishwarya S

•

5. Juli 2020

very nice

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