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

13,082 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....



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.


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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501 - 525 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Nand B P

27. Juni 2017

Best Introductory course for Machine Learning for beginners as it shows an abstract yet hands-on type of approach to cover all the important topics related to the ML concepts.

von vivek m

3. März 2017

Best course to get start with ML as it has lot of real world example to get your hand dirty, which will help us to develop approach 'how to solve real world problem using ML '

von Farouq O

3. Feb. 2016

The course did a good job of balancing depth with breadth. It's a well rounded course that provides a a student with enough information to tackle intermediate-advanced topics.

von Alexander B

12. Dez. 2015

Very best initial level course that will introduce anyone to one of the modern ml tools and its usage, with a bit of needed theoretical science (its only an approach aint it?)

von Sagar S

7. Juni 2020

This is a very well designed course to build the Machine Learning Foundations for any level. And also its a perfect segway to remaining detailed courses of the Specialization

von Shah H

6. Dez. 2019

Enhance my knowledge in ML and skilled me to do best Research in my MS Study, Thanks to COURSERA and University of Washington to give financial aid to learn Machine Learning.

von Parth P

1. Apr. 2018

Hey This is Excellent course for beginners. The homework assignments are designed to grasp concepts easily and in most practical way possible. Thanks for such a great course.


11. März 2018

Very interesting, useful, and up to date, this course gives the main ideas with clarity, and relevant applications, in a time format that is feasible for an active engineer.

von Dheeraj A

28. Okt. 2016

Course combines Real Word Applications with simple implementation via IPython Notebooks. Professors

know their stuff but are super chill. Pretty good assignments and quizzes.

von Scott W

10. Juni 2016

Great way to warm up the class. Seeing how the various techniques and best practices should/can be used was very helpful in warming up for the more densely focused classes.

von Omri R

29. Feb. 2016

This is a great intro to a range of topics in machine learning. I do recommend pursuing the entire specialization since this course only scratches the surface of each topic.

von Marcus C

8. Feb. 2016

great course. This covers all types of machine learning techniques deep enough to get a basic idea how things work. Enjoyed a lot. Instructors are really fun to learn from.

von Cissy S

2. Dez. 2015

Loving it so far! Can't wait for the other courses. The case study approach is spot on! This is the first coursera course that is worth something! Kudos to the instructors.

von Pankaj K

25. Sep. 2017

Nice overview to ease into all the content!, Only bad this is they use sframe :( either make it opensource and in the mainstream use or provide the assignments in sklearn!


15. Feb. 2016

A very informative beginners cource which offers a macro view of different approaches to MachineLearning and prepaes the student for further study in each different areas.

von Kirill L

3. Feb. 2016

Great for a start.

Still has some issues for those who use sklearn and pandas.

Also I'd prefer to see more detailed info on neural networks instead of deep learning module.

von Fabian d A G

15. Aug. 2021

E​xcellent course that spans the broad ML domain. Unfortunately it appears that the specialization ends sooner than what was planned, but remains quite good nevertheless.

von Vishal A

29. Nov. 2017

They have used graphlab instead of using standard library. But overall good course.

If the student can submit quiz question without enrolling then it would be a big plus.

von Amy M

11. Juli 2017

The instructors were fantastic, the material was understandable, and the reach I have beyond this course is still expanding. Thank you for a wonderful learning experience

von Dan S

13. März 2016

I found this course as a great introduction to the world of machine learning with a very practical approach.

I'm waiting forward to the next courses in the specialization.

von Thomas K

5. März 2016

I loved this course! It is really well done, that you have a theory part and a practical "case study" part, were you can follow along with the provided IPython Notebooks.

von Eric A J C

17. Apr. 2021

An excellent course to get introduced to the field of Machine Learning. Amazing professors! And actually putting the knowledge into practice with Python was a big bonus.


10. Sep. 2019

This course is designed in a very planned way. It gives you a bird's eye view of the ML world without boggling down you with too much technicalities. Highly recommended.

von Muhammad U C

11. Feb. 2016

A good theory and practical based overview of major machine learning tasks. Hands-on practice using GraphLab Create makes it one of the best courses in Machine Learning.

von Sanath K S

5. Aug. 2020

An immaculate course to get your basics and facts right to get a head start in ML.The mentors did their part well. I strongly recommend the vert course to the aspirants