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Coursera Project Network による Analyze Text Data with Yellowbrick の受講者のレビューおよびフィードバック

4.4
80件の評価
9件のレビュー

コースについて

Welcome to this project-based course on Analyzing Text Data with Yellowbrick. Tasks such as assessing document similarity, topic modelling and other text mining endeavors are predicated on the notion of "closeness" or "similarity" between documents. In this course, we define various distance metrics (e.g. Euclidean, Hamming, Cosine, Manhattan, etc) and understand their merits and shortcomings as they relate to document similarity. We will apply these metrics on documents within a specific corpus and visualize our results. By the end of this course, you will be able to confidently use visual diagnostic tools from Yellowbrick to steer your machine learning workflow, vectorize text data using TF-IDF, and cluster documents using embedding techniques and appropriate metrics. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, Yellowbrick, and scikit-learn pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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Analyze Text Data with Yellowbrick: 1 - 9 / 9 レビュー

by Ali M H

2020年4月14日

It was an amazing test and this lecture i like same with my area teaching.

by Carlos A R Z

2020年6月19日

Analyze Text Data with Yellowbrick is a perfect course :3

by Ronny F

2020年7月25日

thanks for your guidence

by XAVIER S M

2020年5月31日

Thank You !

by Vajinepalli s s

2020年6月18日

nice

by Kevin I L

2021年4月2日

Could have run through the theory behind the library functions a bit more as a refresher but for brevity's sake it is alright the instructor did not.

by MOHAMMED B

2020年6月17日

thanks

by Muhammad S A

2020年6月24日

It was good but it would be nice to have more explanations on the topics.

by Vipin

2020年11月4日

I'd expect at the end using K-means clustering will check with actual labels instead of saying "wow it did a great job". Free youtube videos often do a better job than this !