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
13,082 Bewertungen
3,116 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:

376 - 400 von 3,043 Bewertungen für Machine Learning Foundations: A Case Study Approach

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!

von SATYAM S

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 it...now 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.

von Uduak O

11. Dez. 2015

Excellent course content with emphasis on real-life applications

Great teaching tools and I particularly love the teaching style of Carlos and Emily. Going on with this specialization till the very end.

Great work guys!

von Mehar C S

16. Nov. 2020

It was a really nice way of presenting ML concepts using Case Studies. Giving students an idea of deployment right from the start helps in thinking of an architecture of the system for any project that comes forward.

von Soumen D

16. Nov. 2016

Love the way the subject is introduced. The course increased my interest for machine learning and also made me understand the power of machine learning first hand. Thank you, Prof Carlos , Prof Emily and entire team.

von Pedro

20. Juli 2017

Un curso muy bien explicado, fácil de entender y unos profesores que consiguen mantener la atención y absorberte en el tema.

Lo recomiendo 100% para iniciarse en los modelos y entender los algoritmos simples de ML.

von Brian S

27. Sep. 2017

Loved the case study approach and how it relates to real world problems. Utilizing graphlab also helped abstract away a lot of the details, but I look forward to diving deeper with the rest of the specializations!

von Luiz B J

17. Feb. 2022

Excelent material and instructors. There is at least one of the assignments that needs reviewing because probably the data has changed since the first time the course was offered but the autograder wasn't updated.

von anirban d

19. Aug. 2019

This stream along with Andrew NGs is the best ML course available in Coursera. The lectures, especially from Emily's are one of the best. It is perfect for both experienced and newbies. Thanks, Emily and Carlos.

von Shekhar P

5. Apr. 2016

Awesome course ....Both Professors are very intelligent and teaching perfectly....Step by step explanation and also never feel bore because presentation styles are also very best. Thanks professors and Coursera.

von Aniket R

6. Feb. 2016

The case study approach makes it fun to learn machine learning. The introduction to various topics through specific examples increases curiosity and sets the tone for the following courses in the specialization.