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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
13,082件の評価
3,116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.

The forums and discussions were really useful and helpful while doing the assignments.

フィルター:

Machine Learning Foundations: A Case Study Approach: 401 - 425 / 3,043 レビュー

by ROBIN S 1

2020年12月10日

Thoroughly enjoyed this course! Really loved the case study approach of teaching. The instructors are excellent as well, throughout the course it felt like I was hanging out with my friends building cool stuff!

by Alessio D M

2015年12月7日

I think the course is really COOL :) I know that it's really hard to cover so many topics, but I would have been curious about the area of reinforcement learning too. Perhaps mentioning MDPs and related models.

by Lin V

2016年2月20日

Thank you very much for providing us this cool and exciting course. Thank you, Emily and Carlos. It opens a door for me and I've really enjoyed ML so far. Hope one day I could be part of the UW. All the best.

by Cristina E

2016年2月12日

Very good explanations and well-thought out assignments and practical exploration. The usage of the proprietary GraphLab software was a minus, but since it was used just for exploratory purposes, no harm done.

by Hossein N S

2016年2月9日

This course was very usefull tome as it was implemented in a way that it's easy to understand the core of the module and the subject.

I understand and it prepared me for the rest of the Machine Learning courses

by Ethan G

2015年11月22日

This was a great intro course to the topic, and the instructors both make complicated concepts accessible. For example, the explanation of non-linear features in deep learning is extremely clear and intuitive.

by PRAVEEN R U

2018年8月23日

This will be really helpful for someone who really wants to start the ML journey and not sure where to start. The content was designed well to suit people across levels and technologies. Strongly recommended.

by SANDEEP

2018年7月27日

To define how machines can learn, we need to define what we mean by “learning.” In everyday parlance, when we say learning, we mean something like “gaining knowledge by studying, experience, or being taught.”

by Carlos A M

2021年1月18日

Pretty Cool as Foundations in ML!!! If you already have expertize on Pandas and python you would find this course as a good entry point for Machine Learning as the point of view is 50/50 theorical/practice.

by Adrian L

2020年7月10日

Friendly introduction to basic concepts and how to put them in practice to start diving into the exciting ML world that is all around us nowadays, specifically during current uncertain and challenging times.

by Lokesh K

2019年1月26日

I appreciate the effort you kept for this online course.Actually I enjoyed learning here.But you can be little bit more detailed in the ipython notebook code explanation. Otherwise ,this is the best course .

by Ramesh K

2016年2月8日

Course is really taking a practical approach towards machine learning, with theory and practical classes side by side. Thanks to Course era and University of Washington for providing a wonderful opportunity.

by DURGESH G

2020年6月21日

This course will provide a deep and elaborated knowledge about basics of machine learning and deep learning. Both the instructor Emily And Carlos are very good they cover each and every point of discussion.

by ANIMESH M

2020年6月8日

Such an amazing course.

It opens all the uncovered secrets behind Machine Learning .

With best mentors and enough practice i had gain thorough knowledge and interest toward Machine Learning.

Above Expectation.

by Muhammad H T

2020年5月4日

Amazing course by Carlos Guestrin and Emily Fox both have the deep knowledge of their domain and more over they also have the skills of how to teach. Love you both Carlos Guestrin (Sir) and Emily Fox (Mam)

by Rania B

2019年1月6日

I had to use TuriCreate instead of GraphLab, so other than the changes in the libraries that had me guessing which function to use, everything in this course is well structured and concrete. Thank you all!

by 黄怡

2018年5月29日

Actually, this course is the best introduction for machine learning for me .

it gives me a outline of machine learning structure . thankful , and i will continue learn other courses in this whole course .

by Olga V

2017年7月7日

Great course giving an overview helping get a sense how machine learning is applied. Material is delivered well and concisely. Like the data sets used for examples, because they are interesting to explore.

by Eik U H

2017年6月27日

A real breathtaking great course about the basics of machine learning with very concise materials. Unfortunately died after four parts. I'am hoping for resurrection with a part 5 and 6.

Thank you very much.

by Lucas d L O

2016年8月9日

Great course for understanding introductory principles of the different areas of Machine Learning. The classes are very well taught and the exercises are very interesting. Highly recommended for beginners!

by Guillermo R

2018年5月13日

I really enjoyed the foundations course. It did exactly as I expected - it gave a great overview of machine learning concepts to prepare for the upcoming in-depth modules. Emily and Carlos were fantastic!

by Kan B

2016年10月24日

Very good approach. Let students hands on and play with ML model first, before jumping into details. In real life, understanding use cases is really important before investigating more time into theories.

by jeevanjot s

2018年10月29日

Very good foundations course for beginners.....might be a little too basic for people who have experience in ML, but nonetheless good for refreshing your knowledge. Absolutely love the sue case approach.

by Pranav V V

2017年10月15日

The course provides a good overview of different ML approaches - Regression, Classification, Clustering, Neural Networks. The approach of using exercises to answer quiz helps in practicing the concepts.

by Eftychios V

2016年6月25日

I really liked the case study approach. It starts from real life examples and shows you how simple it is to make your own models and predictions which really lures you into the machine learning concept.