Voltar para Analyze Text Data with Yellowbrick
Comentários e feedback de alunos de Analyze Text Data with Yellowbrick da instituição Coursera Project Network
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Sobre o curso
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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1 — 9 de 9 Avaliações para o Analyze Text Data with Yellowbrick
por Ali M H
•14 de Abr de 2020
It was an amazing test and this lecture i like same with my area teaching.
por Carlos A R Z
•19 de Jun de 2020
Analyze Text Data with Yellowbrick is a perfect course :3
por Ronny F
•25 de Jul de 2020
thanks for your guidence
por XAVIER S M
•31 de Mai de 2020
Thank You !
por Vajinepalli s s
•18 de Jun de 2020
nice
por Kevin I L
•2 de Abr de 2021
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.
por MOHAMMED B
•17 de Jun de 2020
thanks
por Muhammad S A
•24 de Jun de 2020
It was good but it would be nice to have more explanations on the topics.
por Vipin
•4 de Nov de 2020
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 !
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