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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

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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2576 - 2600 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

von mikhil i

1. Dez. 2016

The deep learning part of the course needs to be better done. The rest is good

von Ricky W

10. Feb. 2016

Very nice introduction to Machine Learning and to Python programming language

von Max D

23. Aug. 2021

id like to see more examples and use others packages different to turicreate

von Daniel B S d S

2. Nov. 2016

The course is great, but it would be greater if used open source free tools.

von Igor S

13. Apr. 2021

I would improve questions in the quiz, sometimes they are really confusing.

von Bilal S

17. Okt. 2016

It' a fine beginner's course. I liked the hands-on approach using SFrames.

von Marco P

4. Dez. 2015

The homework assignments were not really about having understood the course

von Sourabh K

30. Juni 2020

numpy and pandas are more preferable, but the overall experience was good.

von George B

17. Mai 2018

Pretty great course. Really enjoyed it and looking forward to new courses

von Jeffrey v S

31. Okt. 2017

Content is good but the delivery is somewhat awkward and chatty at times.

von Brennan W

4. Feb. 2017

Was a good intro to different kinds of ML. Wish we had used SciKit-Learn.

von Nandan S

15. März 2018

very good overall. The last week (Neural networks) is a little too fast.

von Ramesh S

14. März 2018

A good and quick introduction to ML. Like the Case Study based approach.

von Anastasiia

2. Feb. 2018

OK course if you don't have any background knowledge. Graphlab oriented.

von Aaron M

2. Juli 2017

Seems a bit old but it was a great way to introduce myself to the basics

von Matías G

7. Okt. 2016

Great Course, just felt little weak the last module about deep learning.

von Stuart L

18. Dez. 2015

a good introduction of the topics. I like the ML diagram in each module.

von Thirumala V S J

10. Feb. 2022

Course is kind a old and some dependencies are not working as explained

von Lucia d E P

5. Feb. 2018

I enjoyed the course and the fact that it uses Python for the exercises

von Xavier H

8. Aug. 2016

A good introduction tot he tools and possibilities of machine learning.

von Zhe W

27. Okt. 2015

Useful course to get general idea to get onboard with Machine Learning.

von Leon

1. Okt. 2019

Goes through many topics, but not as in depth as one would have liked.

von Jacques J

8. Sep. 2017

Was so good to get some exposure to the different areas of application

von Sandeep K S

5. Jan. 2016

Good course with the overview of different machine learning techniques

von fredfoucart

10. Dez. 2015

A good global introduction and simply explained. With fun as well....