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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

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

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.

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2601 - 2625 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Ali N

13. Nov. 2015

Really great course content, but the assignments could become better.

von Harshal M

18. Aug. 2017

Great Course!! Helped me learning new things. Great way of teaching.

von federico w

4. Apr. 2016

Great course. Super case driven approach, professors are very clear.

von أحمد ج

6. Aug. 2019

wish to use more common ML libraries, but the content was very good

von Kushvanth R

21. Jan. 2021

All is well, but instructors could have used more common libraries

von Bruno G E

17. Apr. 2016

Just the tip of the iceberg, you'll want to dive in on each topic.

von Tina W

2. Apr. 2019

Good Intro course and familiarize yourself with iPython notebook.

von sami j

26. Dez. 2017

pretty good - wish there was more info on the internals to models

von Alexander P

17. Okt. 2016

Interesting intro class. Will very much leave you wanting more.

von Paul B

21. Juli 2016

Good introduction, the python quick description is short enough.

von Pramod J

17. Okt. 2020

Contents are up to mark and very helpful in learning the course

von Kunal B Y

25. Juni 2020

it will be better if the videos are also updated to turi create

von Mandar G

31. Mai 2020

Both the Instructors were very good at providing the knowledge!

von Anurag U

2. Nov. 2016

Its a good course for those who want to learn ML with Graph Lab

von Ahmad B E

5. Dez. 2017

Good course for ML except it depends a lot on GraphLab Create.

von James S

7. Okt. 2016

dont really like the dependency with dato sframe or prop tools

von Paolo s

5. Okt. 2016

It would be perfect if also cover a section on spark an mllib.

von Marco J

14. Jan. 2022

Klasse Kurs, nur bei Graphlab vs. Turicreate etwas verwirrend

von yangxiaoqi

29. Jan. 2018

可以在刚入门机器学习时候听一听这门课,能够知道机器学习在实际中如何应用的。但是要深入机器学习还是应当学学里面的数学知识的。

von Johan M

9. Juni 2016

Excellent course. Looking forward to the rest of the courses.

von David B

4. Dez. 2015

A nice introduction to the various machine learning concepts.

von P V P

28. Juni 2020

its very basic just used a python module in the whole period

von SOWMYA P

3. Juni 2020

i understood many more in this course i understood properly.

von kumar p

15. Okt. 2015

Nice for learners who want to jump start in machine learning

von Swapnil A

6. Sep. 2020

Would have been a 5 start course if the content was updated