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

13,022 Bewertungen
3,098 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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2726 - 2750 von 3,022 Bewertungen für Machine Learning Foundations: A Case Study Approach

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


16. Mai 2022

Nice Content


30. Nov. 2021

good teacher

von Rupali G

2. Nov. 2017

good content

von André G

14. Mai 2016

Good course.

von 廖敏宏

24. Sep. 2020

Very useful


18. Sep. 2020



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


von Aishwarya S

5. Juli 2020

very nice

von Zhen W

5. Juli 2017

Good ~~~~

von Kevin C N

10. Dez. 2016


von Oriol P

30. März 2016

Was nice!

von Sreemannarayana B

23. Feb. 2016


von Oumar D

21. Feb. 2016



21. Sep. 2020

Like it.

von John M

4. Juli 2018

Liked it

von Phoenine

23. Dez. 2018

So good