Chevron Left
Zurück zu Machine Learning Foundations: A Case Study Approach

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

4.6
Sterne
13,101 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

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.

Filtern nach:

2676 - 2700 von 3,049 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Flavio B

9. Feb. 2016

von GOLLAPUDI R C

23. Nov. 2015

von Charupriya S

21. Juli 2020

von Sankara S K

22. Sep. 2018

von Nil K P

10. Juni 2020

von Jakkamsetti S D

27. Apr. 2020

von Om D

4. Dez. 2019

von Oleg S

21. Juli 2017

von JUTUR S V

24. Juni 2020

von Alberto M

21. Sep. 2018

von Neilmani S

13. Feb. 2018

von Yang W

10. März 2016

von Priyanka J

18. Juni 2020

von Abhinav M

1. Apr. 2018

von Dominik S

26. Juni 2017

von Sunny D

3. Mai 2020

von Shishir S

28. Mai 2017

von kulbhushan

27. Okt. 2016

von BIAN D

15. Juni 2016

von A d v

9. Jan. 2022

von Royal P

18. Nov. 2020

von Reginald A L

20. Sep. 2020

von Li Y

15. Okt. 2017

von Yunqi H

24. Jan. 2020

von Nitin K

4. Mai 2017