From the course: Natural Language Processing in Python
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Solution: Sentiment analysis - Python Tutorial
From the course: Natural Language Processing in Python
Solution: Sentiment analysis
To work on the assignments for this section, I'm going to go to the course materials, course assignment notebooks, and I'm going to make a copy of this section for assignments notebook. So I'm going to click duplicate, and then rename, and I'm going to rename this with my name. And now if I open that, I can start working on the machine learning assignments. So the first step here is to create a new NLP machine learning environment. We just walked through that in the demo a few lessons ago on creating a new environment. The main differences between this new environment and the one from the prior section is within this one, we can now open up Excel files using OpenPyXL. And we can also now do sentiment analysis using Vader sentiment. So make sure you have those two installed. If you need the code to do that, you can find them in the section for solutions notebook. Now within that environment, you're going to launch a Jupyter notebook, which we've done at this point and the next step is…
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Contents
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Section introduction1m 20s
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What is machine learning (ML)?2m 55s
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Common ML algorithms for NLP2m 51s
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Traditional NLP overview2m 31s
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Traditional vs. modern NLP1m 55s
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Demo: Create a new environment4m 9s
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Sentiment analysis1m 28s
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Sentiment analysis in Python2m 46s
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Demo: Sentiment analysis in Python6m 11s
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Assignment: Sentiment analysis58s
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Solution: Sentiment analysis8m 50s
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Text classification basics1m 51s
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Text classification algorithms2m 6s
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Naive Bayes8m 4s
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Naive Bayes in Python3m 8s
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Demo: Naive Bayes setup9m 19s
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Demo: Naive Bayes workflow8m 33s
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Demo: Naive Bayes prediction3m 8s
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Pro tip: Compare ML models8m 56s
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Text classification next steps3m 11s
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Assignment: Text classification1m 25s
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Solution: Text classification14m 3s
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Topic modeling basics2m 16s
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Topic modeling algorithms1m 42s
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Non-negative matrix factorization (NMF)4m 22s
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NMF in Python2m 28s
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Demo: Fit an NMF model5m 1s
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Pro tip: Display topics function9m 30s
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Demo: Tune an NMF model8m 51s
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Topic modeling next steps1m 56s
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Pro tip: Combine ML algorithms5m 3s
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Assignment: Topic modeling1m 45s
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Solution: Topic modeling13m 5s
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Key takeaways2m 57s
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