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Machine Learning Foundations: A Case Study Approach に戻る

ワシントン大学(University of Washington) による Machine Learning Foundations: A Case Study Approach の受講者のレビューおよびフィードバック

4.6
13,029件の評価
3,100件のレビュー

コースについて

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....

人気のレビュー

BL

2016年10月16日

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

2019年8月18日

The course was well designed and delivered by all the trainers with the help of case study and great examples.\n\nThe forums and discussions were really useful and helpful while doing the assignments.

フィルター:

Machine Learning Foundations: A Case Study Approach: 76 - 100 / 3,025 レビュー

by Peter F

2020年3月30日

This course would be okay if it weren't for turicreate, a Python package that's supposed to simplify things. If you have Linux or a Mac, it will do just that, but if you have Windows steer well clear of this course. The lecturers haven't considered the possibility that anyone might not have Linux or a Mac. All the faffing around getting turicreate to work (I did it once and I'm not doing it again) wasn't worth my trouble so I ended up guessing the answers to the quiz questions (you're allowed three attempts every eight hours) just to get this course out of the way. I'll use something actually accessible for the remaining courses, namely R.

by Rithik S

2020年5月26日

The files that are given in readings are unable to open and turicreate cannot read that files also. I cant complete my assignments without reading those files. They haven't given any detailed explanation about how to read those files. In videos they had explained through csv files but in assignments they had given sframe file which are unable to read

by Yakubu A

2020年12月23日

The learning tools and environment is not friendly. The use of graph lab seem outdated since python 3.7 does not seem to support the module. I suggest the course be reviewed. Python 2.7 seem to be going out of the system so something should be done about this

by ye

2021年1月31日

The course is limited to use special package - turicreate, sframe, no detailed explanation of how to install that. Packages used are very out dated

by Jitendra S

2016年4月29日

Dato tool does not even install properly.. so n´makes no sense to continue with the course. The support team fail to help in installing ... :-(

by Ashutosh N

2020年5月30日

The course is explained using turicreate , which does not work in windows properly. It should have been explained using open source libraries.

by Krupesh A

2019年2月15日

Uses very old versions of libraries. Many students are facing issues which remains unsolved. Not recommended to pursue it.

by Shreyash N S

2020年5月20日

graphlabcreate creates many problem while working..it should be changed

by Japman S

2020年6月6日

Based on Python 2 libraries not working on python 3. Obsolete Course

by YM C

2019年9月6日

Too old, bad packages, not much to learn. too basic.

by Darren R

2015年10月13日

Thoroughly disappointed to see this course based on

by Kaushik M

2016年5月1日

Too many videos and not cluttered assignment codes

by D. F

2021年2月2日

Out of date material. Poor instruction

by Rohit

2020年4月19日

This course is pretty good for beginners. All domains are explained briefly as an introduction. The best part about this course is very good hands-on sessions which are really helpful to understand concepts. The course is not very detailed but it's very good to start with. Looking forward to quality courses ahead in this specialization.

by Shibhikkiran D

2019年4月13日

This is course is very informative for a beginner. It helps you to get up and running quick provided you have little basics on Python. You should( sideline on your own interest) also pickup Statistics/Math concepts along each module to make a rewarding experience as you progress through this course.

by Diogo P

2016年2月15日

With a funny and welcoming look and feel, this course introduces machine learning through a hands-on approach, that enables the student to properly understand what ML is all about. Very nicely done!

by Karthik M

2018年12月27日

A good course to understand the basics of Machine Learning. The only issue is the use of Graphlab library. Since it only works on Python 2.7, it is not convenient for people who prefer Python 3

by Alexandru B

2016年1月21日

Great course. Very informative and inspirational. I got tons of ideas from it! Thank you

by Mallikarjuna R V

2019年1月17日

Wonderful opportunity to learn and execute hands on coding of Machine Learning. The amazing task that Machine Learning methods and algorithms does behind scene is understood for the following cases / intelligent applications:

1. Regression (e.g. Predicting House Price etc.)

2. Classification (e.g. Product review sentiment, Spam detection, Medical diagnosis etc.)

3. Clustering and Similarity (e.g. Grouping news articles)

4. Recommender (e.g. Amazon personalized product recommendations, Netflix personalized Movie recommendations etc.)

5. Deep Learning and Deep Features (e.g. Google image search, Image-based filtering etc.)

The main challenge for me was to code using “Python3, Pandas and SciKit-Learn” instead of “Python2, GraphLab Create and SFrame”. I am now confident to develop intelligent applications based on Machine Learning. Thanks to Professors (Emily and Carlos) and to Ashok Leyland-HR for giving me this opportunity.

by Sundar R

2020年8月19日

The teaching is of good quality and the lectures are easy to follow along. The only downside I thought was week 6 where I felt the topics weren't covered in enough detail in order to clear the quiz. Lastly, very disappointed by the exclusion of courses 5 and 6 which would've made this specialization a complete package.

by akashkr1498

2019年1月18日

lacture was good but one point i want to share to you don't use rare tools for assignment personally i faced lots of problem while installing graphlab better to switch to some common tools like sklearn python platform .

by Yuvraj S

2019年2月1日

It is a good course if we take into account the foundational part. But since only one library has been used to solve the issues, one does not explore and write their own functions.

by Jaime R

2018年12月17日

Great introduction course. However, getting the notebooks to work with Graphlab is a real pain. The notebook exercises are also mostly make-work rather than real explorations. The explanations and the notebooks themselves are pretty good though

by Ezequiel P

2020年11月7日

Excellent Theory. Very clear explanations with simple yet powerful examples. Sadly the practical part is not nearly as good. Mainly because of the tool used. If this was implemented in Scikit-Learn, the course would be excellent overall.

by Ayush G

2020年6月5日

the course seems outdated in many aspects, the support isn't available to clarify doubts and the documentation isn't updated either. Moreover, the software support has ended.