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1. Getting the data for Text Classification.mp4
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62.1 MB
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1. Installing Anaconda Python.mp4
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1. Installing NLTK in Python.mp4
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1. Introduction to Numpy.mp4
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280.7 MB
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1. Introduction to Regular Expressions.mp4
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62.8 MB
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1. Setting up Twitter Application.mp4
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28.3 MB
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5 KB
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1. Understanding Text Summarization.mp4
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95.7 MB
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1. Understanding Word Vectors.mp4
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160.6 MB
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16 KB
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14 KB
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1. Variables and Operations in Python.mp4
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60.3 MB
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1. What is NLP.mp4
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1. Where you go from here.html
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716.8 B
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10. Introduction to Classes and Objects.mp4
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92.4 MB
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10. Named Entity Recognition.mp4
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56.1 MB
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10. Training our classifier.mp4
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30.7 MB
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11. List Comprehension.mp4
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165.5 MB
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11. Testing Model performance.mp4
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84 MB
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11. Text Modelling using Bag of Words Model.mp4
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146.1 MB
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12. Building the BOW Model Part 1.mp4
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88.6 MB
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12. Saving our Model.mp4
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96.6 MB
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12. Test Your Skills.html
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204.8 B
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13. Building the BOW Model Part 2.mp4
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82.2 MB
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13. Importing and using our Model.mp4
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56.1 MB
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5 KB
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14. Building the BOW Model Part 3.mp4
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77 MB
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15. Building the BOW Model Part 4.mp4
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108.1 MB
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16. Text Modelling using TF-IDF Model.mp4
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223 MB
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16. Text Modelling using TF-IDF Model.srt
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22.1 KB
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17. Building the TF-IDF Model Part 1.mp4
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109.9 MB
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17. Building the TF-IDF Model Part 1.srt
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18. Building the TF-IDF Model Part 2.mp4
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122.7 MB
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19. Building the TF-IDF Model Part 3.mp4
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109.8 MB
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2. Conditional Statements.mp4
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63.8 MB
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2. Conditional Statements.srt
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2. Fetching article data from the web.mp4
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43.9 MB
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2. Finding Patterns in Text Part 1.mp4
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79.5 MB
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2. Finding Patterns in Text Part 1.srt
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10.9 KB
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2. Getting the Course Resources.mp4
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18.2 MB
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2. Getting the data for Text Classification - Text.html
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819.2 B
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2. Importing the data.mp4
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54.9 MB
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2. Initializing Tokens.mp4
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35.1 MB
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2. Installing Anaconda Python - Text.html
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716.8 B
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2. Introduction to Pandas.mp4
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251.6 MB
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2. Tokenizing Words and Sentences.mp4
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74.6 MB
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20. Building the TF-IDF Model Part 4.mp4
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64.6 MB
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21. Understanding the N-Gram Model.mp4
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259.2 MB
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21. Understanding the N-Gram Model.srt
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27.1 KB
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22. Building Character N-Gram Model.mp4
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185.7 MB
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22. Building Character N-Gram Model.srt
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20.2 KB
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23. Building Word N-Gram Model.mp4
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160.5 MB
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14.8 KB
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24. Understanding Latent Semantic Analysis.mp4
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194.5 MB
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24. Understanding Latent Semantic Analysis.srt
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19.3 KB
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25. LSA in Python Part 1.mp4
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295.6 MB
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25. LSA in Python Part 1.srt
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26. LSA in Python Part 2.mp4
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190.2 MB
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14.9 KB
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27. Word Synonyms and Antonyms using NLTK.mp4
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118 MB
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28. Word Negation Tracking in Python Part 1.mp4
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90.7 MB
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28. Word Negation Tracking in Python Part 1.srt
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29. Word Negation Tracking in Python Part 2.mp4
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58.6 MB
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3. A tour of Spyder IDE.mp4
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46.8 MB
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3. Client Authentication.mp4
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46.7 MB
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3. Finding Patterns in Text Part 2.mp4
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81.5 MB
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3. Finding Patterns in Text Part 2.srt
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9.9 KB
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3. Getting the Course Resources - Text.html
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614.4 B
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3. How tokenization works - Text.html
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1.6 KB
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3. Importing the dataset.mp4
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57.5 MB
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3. Introduction to Loops.mp4
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64.8 MB
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3. Parsing the data using Beautiful Soup.mp4
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94.3 MB
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3. Preparing the data.mp4
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38.5 MB
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4. Fetching real time tweets.mp4
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80.9 MB
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4. Fetching real time tweets.srt
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4. Fetching real time tweets.vtt
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4. How to take this course.html
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1.6 KB
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4. Introduction to Stemming and Lemmatization.mp4
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107.5 MB
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4. Loop Control Statements.mp4
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62 MB
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4. Persisting the dataset.mp4
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71.6 MB
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4. Preprocessing the data.mp4
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4. Substituting Patterns in Text.mp4
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54.2 MB
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4. Training the Word2Vec Model.mp4
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33.8 MB
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5. Loading TF-IDF Model and Classifier.mp4
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36 MB
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5. Preprocessing the data.mp4
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5. Python Data Structures - Lists.mp4
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129.2 MB
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5. Shorthand Character Classes.mp4
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182.4 MB
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5. Shorthand Character Classes.srt
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5. Stemming using NLTK.mp4
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133.5 MB
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5. Stemming using NLTK.srt
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8.5 KB
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5. Testing Model Performance.mp4
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54.5 MB
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5. Testing Model Performance.srt
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5. Testing Model Performance.vtt
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4.3 KB
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5. Tokenizing Article into sentences.mp4
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50.7 MB
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5. Tokenizing Article into sentences.srt
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3.9 KB
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6. Building the histogram.mp4
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58.6 MB
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6. Building the histogram.srt
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5.4 KB
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6. Building the histogram.vtt
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6. Character Ranges - Text.html
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1.2 KB
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6. Improving the Model.mp4
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108.2 MB
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6. Improving the Model.srt
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6. Improving the Model.vtt
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6. Lemmatization using NLTK.mp4
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76.5 MB
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6. Lemmatization using NLTK.srt
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6. Preprocessing the tweets.mp4
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133.1 MB
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6. Python Data Structures - Tuples.mp4
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60.9 MB
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6. Python Data Structures - Tuples.srt
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Course Downloaded from coursedrive.org.txt
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Visit Coursedrive.org.url
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![Udemy - Hands On Natural Language Processing (NLP) using Python [Course Drive]](/static/img/no-torrent-image.png "Udemy - Hands On Natural Language Processing (NLP) using Python [Course Drive]")
