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

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.

SZ

19. Dez. 2016

Great course!

Emily and Carlos teach this class in a very interest way. They try to let student understand machine learning by some case study. That worked well on me. I like this course very much.

Filtern nach:

76 - 100 von 3,049 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Peter F

30. März 2020

von Rithik S

26. Mai 2020

von Yakubu A

23. Dez. 2020

von ye

31. Jan. 2021

von Jitendra S

29. Apr. 2016

von Ashutosh N

30. Mai 2020

von Krupesh A

15. Feb. 2019

von Shreyash N S

20. Mai 2020

von Japman S

6. Juni 2020

von YM C

6. Sep. 2019

von Darren R

13. Okt. 2015

von Kaushik M

1. Mai 2016

von D. F

2. Feb. 2021

von Rohit

19. Apr. 2020

von Shibhikkiran D

13. Apr. 2019

von Diogo P

15. Feb. 2016

von Karthik M

27. Dez. 2018

von Alexandru B

21. Jan. 2016

von Mallikarjuna R V

17. Jan. 2019

von Sundar R

19. Aug. 2020

von akashkr1498

18. Jan. 2019

von Yuvraj S

1. Feb. 2019

von Jaime R

17. Dez. 2018

von Ezequiel P

7. Nov. 2020

von Ayush G

5. Juni 2020