Intro to Natural Language Processing in Python for AI

Files Included :

1 - Introduction to the course.mp4 (54.58 MB)
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2 - Introduction to NLP.mp4 (32.63 MB)
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3 - NLP in everyday life.mp4 (18.9 MB)
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4 - Supervised vs Unsupervised NLP.mp4 (26.28 MB)
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10 - Stemming.mp4 (7.14 MB)
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11 - Lemmatization.mp4 (10.72 MB)
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12 - Ngrams.mp4 (18.17 MB)
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13 - Practical task.mp4 (60.59 MB)
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5 - The importance of data preparation.mp4 (33.75 MB)
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6 - Lowercase.mp4 (9.37 MB)
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7 - Removing stop words.mp4 (19.79 MB)
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8 - Regular expressions.mp4 (40.65 MB)
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9 - Tokenization.mp4 (7.81 MB)
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14 - Text tagging.mp4 (22.97 MB)
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15 - Parts of speech POS tagging.mp4 (20.59 MB)
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16 - Named entity recognition NER.mp4 (24.04 MB)
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17 - Practical task.mp4 (52.26 MB)
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18 - What is sentiment analysis.mp4 (37.23 MB)
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19 - Rulebased sentiment analysis.mp4 (22.79 MB)
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20 - Pretrained transformer models.mp4 (22.22 MB)
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21 - Practical task.mp4 (31.73 MB)
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22 - Numerical representation of text.mp4 (33.34 MB)
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23 - Bag of Words model.mp4 (11.52 MB)
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24 - TFIDF.mp4 (19.04 MB)
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25 - What is topic modelling.mp4 (56.89 MB)
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26 - When to use topic modelling.mp4 (31.28 MB)
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27 - Latent Dirichlet Allocation.mp4 (44.73 MB)
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28 - LDA in Python.mp4 (30.05 MB)
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29 - Latent Semantic Analysis.mp4 (32.96 MB)
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30 - LSA in Python.mp4 (13.37 MB)
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31 - Building a custom text classifier.mp4 (18.77 MB)
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32 - Logistic regression.mp4 (26.59 MB)
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33 - Naive Bayes.mp4 (8.39 MB)
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34 - Linear Support Vector Machine.mp4 (10.98 MB)
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35 - Introducing the project.mp4 (18.16 MB)
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36 - Exploring our data through POS tags.mp4 (37.99 MB)
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37 - Extracting named entities.mp4 (19.06 MB)
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38 - Processing the text.mp4 (51.29 MB)
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39 - Does sentiment differ between news types.mp4 (20.36 MB)
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40 - What topics appear in fake news Part 1.mp4 (25.03 MB)
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41 - What topics appear in fake news Part 2.mp4 (34.46 MB)
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42 - Categorizing fake news with a custom classifier.mp4 (30.81 MB)
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43 - What is deep learning.mp4 (52.62 MB)
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44 - Deep learning for NLP.mp4 (39.09 MB)
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45 - NonEnglish NLP.mp4 (38.45 MB)
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46 - Whats next for NLP.mp4 (29.69 MB)
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