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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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13,086 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

PM

18. Aug. 2019

The course was well designed and delivered by all the trainers with the help of case study and great examples.

The forums and discussions were really useful and helpful while doing the assignments.

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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2651 - 2675 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Fenjin W

15. Apr. 2016

Great course! Hope the slides gets better annotated.

von Prashant D

16. Juni 2020

The course was awesome and so does the Instructors!

von Yagyansh S K

2. Dez. 2016

Awesome Teaching Technique Used! Kudos To The Team!

von Mitali C

10. Juni 2020

It was Amazing course ,with amazing instructors :)

von Avinash P M

13. Dez. 2016

Assignments could have been little more difficult.

von Alvin B K

17. Aug. 2020

Carlos and Emily are really cool. They're cool 😀

von 吴青

6. Dez. 2017

didn't reach my expectation but still quite good.

von Albert Z

6. Feb. 2016

Hands on should have been more involved/dificult.

von Omar H F A

3. Juli 2020

Very Good introductory course to the field of ML

von Gopinath T

14. Mai 2019

Well structured course with detailed explanation

von Sam P

16. Jan. 2018

A bit light on details but a great first course!

von Qishen S

25. Mai 2017

A good overview of ML and tutorial for graphlab.

von Harsh R

18. Mai 2020

The course is little bit outdated.

please update

von shadab h

18. Nov. 2018

A must do course to start with Machine Learning

von Deleted A

21. Jan. 2019

great class to learn machine learning hands on

von Spike Y

30. Nov. 2017

I like the explaining about ipython notebook !

von Abid A S

3. Aug. 2017

Good one to start learning some basic concepts

von Amilkar A H M

10. Mai 2019

It's a very good introduction to the subject.

von Roberto E

28. Nov. 2016

Interesting but a bit weak for my purposes...

von Matic D B

9. Feb. 2016

Great course. Maybe a little bit too basic.

von Jayant S

22. Okt. 2019

Explanations must be more comprehensible.

von Flavio B

9. Feb. 2016

Most of it I already knew, but was nice.

von GOLLAPUDI R C

23. Nov. 2015

A good introduction to machine learning

von Charupriya S

21. Juli 2020

It's really nice course for beginners.

von Sankara S K

22. Sep. 2018

This is a good 101 course to start ML.