Topic Modeling Text Documents With LDA: Python in Excel Tutorial (Free Files)

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Topic modeling with Latent Dirichlet Allocation (LDA) allows you to extract information from your text documents!

It doesn't matter if you have emails, SMS text messages, Customer Service chats, or free-form fields in an IT system.

LDA topic modeling is useful to ANY professional.

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LDA ALGORITHM TUTORIALS
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Latent Dirichlet Allocation (Part 1 of 2):

Training Latent Dirichlet Allocation: Gibbs Sampling (Part 2 of 2):

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VIDEO CHAPTERS
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00:00 Intro
01:10 The BBC Dataset
02:08 Processing the Text Data
06:34 Training the LDA Topic Model
09:00 Which Docs Have Which Topics?
10:15 Which Words Belong to Which Topics?
11:52 How Many Topics?
14:45 What’s Next?

#pythoninexcel #pythonexcel #pythonforexcel
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Incredibly explained video. Super professional but also accessible

beeson
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Text analytics has got my attention. Still waiting on my extraction at work and can't wait. Got the approval.

michaelt
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Hello! I don’t trust the neural network, and I’m trying to build the algorithm by myself and understand its structure, but it takes too much time, should I understand how the neural network works or should I just trust it looking at the result? What's the problem here?

rryirup
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Is it possible to increase the smartness of a chat bot or neural network? Does it depend on what information is fed to him? For example, if I feed him a textbook on quantum mechanics, will he become smarter? Or does it depend on the initial AI parameters? How is this regulated?

rryirup