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

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

12,441 Bewertungen
2,976 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....


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

19. Dez. 2016

Great course!\n\nEmily 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:

351 - 375 von 2,888 Bewertungen für Machine Learning Foundations: A Case Study Approach

von jose l v

5. Dez. 2015

This is a very practical an easy way to understand what is behind the ML world. Also, there are a set of tools in this course that would let you implement basic smart applications. I am ver pleased for being part of this course.

von Deleted A

16. Sep. 2016

I really enjoyed this course. The case study approach and the IPython hands-on gave a good understanding of the concepts discussed in the lecture videos. I'm looking forward to complete the specialization. Highly Recommended!!

von Patrick N

18. Feb. 2018

I enjoyed this course as a high-level overview of the basics of machine learning. While I liked the use of Jupyter and Python in general, I would have preferred that the course use scikit-learn. Overall, solid and fun course!

von Adil A

14. Dez. 2017

People who likes top-down learning approach should start ML from this course.

Instructors explain basic overview then follow with interesting practical tasks that makes you understand the topic much better.

Highly recommended.

von Gustavo S

30. Okt. 2016

Very cool course. I can say is the best course for intro to a big science called machine learning, have a lot of good real life examples, with gread mathematical understaing of how things works, i thinks is really cool course

von Varun S

7. Feb. 2016

It was indeed a very well designed course that not only gave a great overview of various machine learning techniques, but also gave hands-on experience in implementing those techniques. Loved Dato. GraphLab Create is awesome.

von Sergey T

3. Jan. 2016

It was instructive, easy to follow and fun to learn! Great thanks to Carlos Guestrin and Emily Fox for creating this excellent course! And thanks Coursera for making the high quality educational content available to everyone.

von Lu E

15. Okt. 2017

A very great course !!!!! Two teachers are doing a good job. They use a kind of practical way, case-study, to teach me lots of practical machine learning knowledge. I will learn the next three courses in this specialization.

von Farrukh N A

16. Dez. 2016

I like the approach the course is designed on, starting with basic know how about all machine learning techniques. Later on dedicating a course on each individual approach. I am looking forward to complete my specialization

von Massimiliano C

22. Juli 2017

very good course, complex topics explained through intuitive and practical use cases, in short time provides an overview on Machine Learning and gives the student the chance to go in depth if necessary.

I liked it very much.

von Kenneth L

30. Aug. 2016

An excellent overview of Machine Learning. Whether catching up with nascent developments in the recent years or first diving in, this class provides a stable, well rounded and well thought out starting point on the subject.

von Enrique d P

18. Feb. 2018

Great! I found it really interesting! It's a great introduction to Machine Learning, different areas, solutions and applications. You can apply different methods to real data, but you only need basic programming knowledge,

von Robin H

19. März 2017

Very essential knowledge about how to get on track of ML and it did very handy for the beginner, who has qualified with the criterions of class candidate. Thanks for the effort in the class arrangement and online teaching!

von Thales P d P

15. Jan. 2016

Excellent material to introduce such a broad topic as Machine Learning. The highlight is definitely the video lectures with Carlos and Emily whom never lose sight of the didacticpurpose and target audience for the course!


26. Juli 2020

An amazing course with interesting content and course structure, an in-depth explanation of various machine learning concepts and multiple worksheets that require hands-on practice of the concepts taught in the lectures.

von Jaisimha S

8. Dez. 2016

Very good course. Great material, good challenging programming assignments. Emily and Carlos are superb. --- > Wow. Amazing. Love you know I'm using all the positive feature words in their sentiment analyzer!!!

von Dinesh P

28. Juni 2016

This course fulfills its promises. Foundations and relevant tools are introduced via case study. Both theoretical as well as practical reviews are done before leaving for next topic. All in all, good introductory course.

von Andrew T

6. Nov. 2015

I enjoyed this course a lot! The case study approach is very helpful to quickly understand how to apply the theory to the real world problems. The course materials are very well organized, especially the lab assignments.

von Willem v G

20. März 2018

Both instructors are very good at explaining the concepts of ML. Also the practical part of the course working with Python and Jupyter notebooks definitely helps in understanding the concepts and apply them right away.

von Balaji S

28. Juni 2017

The course is a perfect introduction to machine learning. I hope the upcoming course will reveal the abstraction of algorithms used in this course. The instructors are awesome. The materials are very easy to understand

von Balaji C G

9. Jan. 2017

The case study approach for explaining machine learning concepts is commendable. This kind of approach will not only help in cementing the concepts but helps in making decisions when it comes to real-life applications.

von Robert G

29. Okt. 2015

These instructors are among the very best I have encountered as a veteran of dozens of MOOCs. Their expertise in the subject matter, presentation and pleasant manner made this a highly pleasurable learning experience.

von Abdulrazak Z

15. Jan. 2020

REAL-LIFE artificial intelligence applications. The examples were so good and real match to the reality, so in this course, I wasn't bored by theoretical information but I have seen its benefits with the code I write.

von Daniel A

16. Sep. 2017

Great course covering the key models, concept and applications in machine learning. Instructors showed good pedagogy, teaching complicated concepts in ways easily understood. Requires some basic knowledge of Python.

von Gustavo B

17. Sep. 2016

For me this is the best course for Machine Learning Foundations that I watch. It was challenging for me because I did the assigment with R packages. I hope on the future for doing other courses for the specialization.