Chevron Left
Retour à Machine Learning Foundations: A Case Study Approach

Avis et commentaires pour d'étudiants pour Machine Learning Foundations: A Case Study Approach par Université de Washington

4.6
étoiles
13,083 évaluations

À propos du cours

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....

Meilleurs avis

BL

16 oct. 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 août 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.

Filtrer par :

526 - 550 sur 3,043 Avis pour Machine Learning Foundations: A Case Study Approach

par Deveer B

22 déc. 2019

Very good theory and practical approach. However, some of the assignments are not very clear while explaining the questions due to which sometimes we get wrong results.

par Mohamed A H

23 oct. 2018

The instructors are very professional, straight-to-the-point, and they have a nice sense of humor :)

which made the course much more interesting. Definitely recommended!

par Mykola D

9 juin 2018

I really like this course. I've learned basics of ML. I've really enjoyed the presentation style. The practical part was great. I am looking forward to the next course.

par Franklin F

16 mars 2018

Clear and fun instruction. The course gave relevant and tangible examples of machine learning in practice and the coding was very managable for a non-systems engineer.

par Yeremy T

15 févr. 2016

Great introduction to Machine Learning and the different ML methods. Assignments were not mean to be hard, but practical, which I appreciate. Great instructors as well!

par Jagdish B P

20 juil. 2019

This is a fantastic course. The concepts are explained so well and are followed by hands-on which helps a lot. Case Study approach really is working well in this case.

par Dennis S

28 avr. 2017

Great presentation of the topic and fitting complexity / depth for an introduction.

Way better then all the other courses i tried before. Great instructors and concept!

par Zeph G

1 janv. 2016

This is a nice introduction to the concepts that will be covered in the specialization and the power of the provided GraphLab Create ML toolbox. I highly recommend it.

par Gwendolyn G

24 nov. 2015

This is a really good intro course. It's not pitched at a terribly high level of difficult, but it does give you a fair amount of practice. I'm really pleased with it.

par Satish K D

25 nov. 2018

Very informative in basics of Machine Learning. It sets the stage for a deep dive into the topics of machine learning like Regression, Classification, Clustering etc.

par Chengran Y

2 mars 2018

This course is really useful, as a overview of the whole specialization. The quiz for theory and python implementation strengthen the key points for each module/week.

par Uday A

14 juin 2017

A perfect introduction to ML. Couldn't ask for more. 6 weeks of coverage is neither shallow nor too deep. Sets up the stage nicely for a deeper dive in next sessions.

par Vaibhav O

25 déc. 2016

Great course to begin your journey into ML

Briefly introduces each topic to give a jist about it and also provides a good starting point for using python in ML context

par Angel G C

13 déc. 2015

In a couple of Case Studies it gives you a wide idea about the almost unlimited potential of Machine Learning while it encourages you to learn more and more about it.

par CO17 3 G

7 juil. 2020

it was really amazing to learn from these mentors. They were really humble, clear and had an interesting way to teach. I would love to attend more of them in future.

par Deleted A

18 sept. 2018

This course gives a really easy but clear concept for machine learning with examples! I hope I can learn something further with other courses in this specialization.

par William C

22 oct. 2017

Fantastic course, great 'learn-by-doing' introduction to ML, really entertaining teachers kept me alert throughout each session. It was great fun and I learnt a ton!

par Sergio B S M

12 juil. 2020

The course is very well structured, interesting lectures with real-life applications, and the programming examples and assignments were very useful and instructive.

par Stefan v D

4 févr. 2020

A great foundational introduction to Machine learning concepts. Ideal for people that have some background in maths and programming but no career in this direction.

par Prashant S

19 oct. 2018

This is a brilliant stepping stone for Machine Learning world. Basics are being discussed and explained in a very simple manner. thanks to the teachers and Coursera

par Shital M

20 nov. 2017

Fantastic overview of various machine learning methods. Very interesting way of exposing concepts using case study approach which makes it more engaging and useful.

par Fernando M P

10 août 2017

This course is a wonderfull introduction to the Machine Learning. It provides a good start point which is very helpful with the other courses of the specialization.

par Fabricio N

27 mars 2016

Best course in data science out there. Believe me, I did all 4 other Specialization, some of then very good, some of then no quite si, but this one is far the best.

par Chris H

24 déc. 2015

A great introduction. Good relevant examples and thoughtful data sets were provided for the exercises. Both lecturers were engaging and clearly knew their subjects.

par Muhammad M

21 juil. 2020

The course is easy and good for beginners. Specifically, case study approach is quite good and furthermore hands on practice assignments greatly improves learning.