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

13,083 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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301 - 325 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

von Supriya N P K

9. Dez. 2015

Its a very basic course and a good start to learn Machine Learning.

Course was pretty easy to follow and the real world examples helped to visualize the applications of Machine Learning. Its highly recommended for the students who are completely new to the Machine Learning.

von amal s

28. Apr. 2020

The course was awesome and i am willing to learn all the courses present in this specialization.Both the tutors are great and their explanation was incredible . Actually this course period is of 6 weeks but I completed the whole course within a week because of the tutors .

von Peter G

26. Feb. 2016

Very nice brief introduction into the field. Gives good overview of main concepts: 1) statements of problems in machine learning 2) approaches to finding solutions 3) methods to evaluate resulting solution . Systematic material presentation with good examples and analogies.

von Zachary N

13. Dez. 2015

Great overview of machine learning techniques and practices at a high level! There is sufficient material here to go from no machine learning knowledge (and a general programming background) to being able to create and deploy machine learning models for use in applications.

von Aman A

26. Mai 2016

Awesome way of teaching that too from a well qualified faculty. Rather than imparting theoretical knowledge, great focus is on practical knowledge that's what I like about this Course. Thanks to Coursera for giving me this opportunity to get tutelage from such an erudite.

von Mayuresh W

23. Nov. 2015

The course was well detailed and gave a good idea of what to expect when learning about machine learning and this specialization.

Covering each of the topics well with sufficient explanation and a small project was a great way to learn.

Looking forward to the next courses :)

von Gérard Y

27. Juli 2018

Very good overview, the lectures were enjoyable to follow, and brought good intuition on the topics with a good sense of what was possible. The exercises were of reasonable difficulty, and not too hard to set up, allowed to get a good feel of the potential of Turi Create.

von gaoyu_xinghuo

20. Juni 2016

Exclude the last part, the whole session gave us the clear picture about machine learning -- What the machine learning is , how machine learning works and how to use machine learning to change the world:)

I love the course, it gave me a lot. Thanks Emily and Carlos again.

von Daniel R

7. Feb. 2016

It is a really well thought introduction for Machine Learning. It is almost unbelieveable that you could use every single technique in less than a month. Of course using a framework, but if you are really interested you could do them with open source tools.

It is amazing!

von Arjun P

24. März 2020

A very good course that gave me a jump start to machine learning application and got me right into coding the applications. This course takes a very different approach to teaching ML and I guess it works as it keeps me interested and makes me want more from this course.

von alexandre l f

22. Okt. 2017

Case study base approach makes this course pragmatical and business oriented. A great team with good tools and exercise which deserves a 5.

Note : math's background is low (or more exactly far from the target of this course) and might be a blocking point at some stage.

von Raphael K

29. Feb. 2016

Nice class, give a brief introduction to all the methods use in ML without going deep. If you just want to get an idea of what ML Technics are and how to implement them this course is for you. If you are want more technical details about ML this class is not for you.

von Yaobang C

29. Aug. 2018

I am very grateful to the coursera platform for giving me the opportunity to learn, and I would also like to thank the two professors for their careful preparation of the wonderful lectures. I learned about machine learning and fell in love with ipynb, thanks again!

von Jose N N P

30. März 2018

Excellent course and very challenging, most importantly, I have learned a lot and I have a great understanding of what machine learning is. Dr. Carlos and Emily are great instructors, and indeed engaging as well as passionate. Looking forward to taking the next one.

von Easton L

25. Feb. 2017

Emily and Carlos are really exciting teachers. This course covers fundamental concepts of Machine Learning and comes with very practical assignments. I've learned a lot from the this course and I believe it will make me ready for more challenging work in the future.

von Alan B

14. Mai 2020

Material was presented in a practical way, making it useful to relate the theoretical concepts to real life applications.

One suggestion might be to speed up the video while typing comments and mistakes while typing, etc. just to make the experience more enjoyable.

von Martin K

26. März 2016

First of all I want to thank you for conducting this course. I have learned a lot from the course. This course gave me basics understanding of machine learning. You did a good job presenting complex machine learning algorithms in a way that everyone can understand.

von don-E M

13. Dez. 2015

I have loved this course. The approach to learning is most fruitful as I have learned a great deal and had a lot of fun along the way. I am on the last exercise to finish the class after about 4 days. I am going to savor this last one because this was too much fun.

von Anatoly M

16. Apr. 2017

Great introduction to machine learning, not too much math but gives a good idea of what ML is + gives practice in Python (which was my initial goal).

The tests contained a few inaccuracies (they didn't completely match on my machine/setup), but otherwise was fine.

von Ravindra P

26. Mai 2020

Great Course to start with machine learning. When I started this course I heard bad words about turicreate. But I think it is very easy to work with this compare to pandas. And it will even save your time that you can invest in learning more theoretical aspects.

von Vinay S

1. Juni 2016

Very interesting and fun course for really complicated topic. The best part of the course is the recommended software tools they are brilliant designed especially graphlab.create. Both the instructors are really engaging and teach complicated topics really well.

von Ravindra M

8. Dez. 2015

Case study approach works !

I completed this course and found course materials present intuitive. Following courses go deep in each method.

Thank you Emily and Carlos :-)

A small request to Coursera to provide course completion certificate to free account like Edx.

von Varun M

12. März 2018

The course starts from very basic level and allows to apply the knowledge practically right from the start so the learner can start to see the results right away which makes it interesting and addictive to jump to next session or video to gain more knowledge.

von Rick P

13. Aug. 2016

Emily and Carlos provide a very fun and informative introduction to ML! I really appreciated getting a "blackbox" overview of the various ML methods before doing a deep dive into the algorithms. GraphLab and the interactive iPython sessions are great!

von mohammed e e

8. Feb. 2016

it's the best course of machine learning i'have token in my life,the method of teaching is great, the content is really fantastic, the instructors teaching skill is excellent and it cover lots of real world artificial applications so it's very amazing