Minor updates to Readme

[brooksjessup]

What you'll learn:

• Would it be better to drop the reference to cosine similarity here as an "unsupervised method" along the lines of tf-idf and topic modeling?
• Would "word embedding" be better than "word vector representations" here? (tf-idf also involves vectorizing words)

Resources:

• The CTAWG website is mostly inactive (maybe link to the working group page on the D-Lab website instead?)
• Update the Stanford course linke to https://web.stanford.edu/class/cs224n/
• Might add the Coursera specialization: https://www.coursera.org/specializations/natural-language-processing

[EastBayEv]

Hi @brooksjessup -- Can you commit and push these changes? Please close this comment when you are done. Let me know if you have any questions. Thanks!

[pattyf]

@j. Brooks Jessup <[email protected]> You can add edx classes <https://www.edx.org/course/introducing-text-analytics-and-natural-language-processing-with-python> too since, unlike coursera, they are free to uc berkeley people.

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On Thu, Feb 11, 2021 at 1:53 PM Evan Muzzall ***@***.***> wrote: Hi @brooksjessup <https://github.com/brooksjessup> -- Can you commit and push these changes? Please close this comment when you are done. Let me know if you have any questions. Thanks! — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#6 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAQGZYNTCHCGSDF3RJJDCETS6RGUTANCNFSM4VRTN5TQ> .

-- Patty Frontiera, PhD Data Services Lead, Social Sciences Data Lab Co-Director, Berkeley Federal Statistical Research Data Center 356 Social Sciences Building, University of California Berkeley http://dlab.berkeley.edu