Natural Language Processing with Python: 3-in-1

سرفصل های دوره

Build solutions to get up and speed with new trends in NLP. Three complete courses in one comprehensive training program

1. Natural Language Processing with Python

1.1 Natural Language Processing with Python_A Complete Guide.zip

1. The Course Overview

2. Installing and Setting Up NLTK

3. Implementing Simple NLP Tasks and Exploring NLTK Libraries

4. Part-Of-Speech Tagging

5. Stemming and Lemmatization

6. Named Entity Recognition

7. Frequency Distribution with NLTK

8. Frequency Distribution on Your Text with NLTK

9. Concordance Function in NLTK

10. Similar Function in NLTK

11. Dispersion Plot Function in NLTK

12. Count Function in NLTK

13. Introduction to Recurrent Neural Network and Long Short Term Memory

14. Programming Your Own Sentiment Classifier Using NLTK

15. Perform Sentiment Classification on a Movie Rating Dataset

16. Starting with Latent Semantic Analysis

17. Programming Example of Principal Component Analysis

18. Programming Example of Singular Value Decomposition

2. Text Processing Using NLTK in Python

1. The Course Overview

2. Accessing In-Built Corpora

3. Downloading an External Corpus

4. Counting All the wh-words

5. Frequency Distribution Operations

6. WordNet

7. The Concepts of Hyponyms and Hypernyms Using WordNet

8. Compute the Average Polysemy According to WordNet

9. The Importance of String Operations

10. Getting Deeper with String Operations

11. Reading a PDF File in Python

12. Reading Word Documents in Python

13. Creating a User-Defined Corpus

14. Reading Contents from an RSS Feed

15. HTML Parsing Using BeautifulSoup

16. Tokenization - Learning to Use the Inbuilt Tokenizers of NLTK

17. Stemming - Learning to Use the Inbuilt Stemmers of NLTK

18. Lemmatization - Learning to Use the WordNetLemmatizer of NLTK

19. Stopwords - Learning to Use the Stopwords Corpus

20. Edit Distance - Writing Your Own Algorithm to Find Edit Distance Between Two Str

21. Processing Two Short Stories and Extracting the Common Vocabulary

22. Regular Expression - Learning to Use , +, and

23. Regular Expression - Learning to Use Non-Start and Non-End of Word

24. Searching Multiple Literal Strings and Substrings Occurrences

25. Creating Date Regex

26. Making Abbreviations

27. Learning to Write Your Own Regex Tokenizer

28. Learning to Write Your Own Regex Stemmer

3. Developing NLP Applications Using NLTK in Python

1. The Course Overview

2. Exploring the In-Built Tagger

3. Writing Your Own Tagger

4. Training Your Own Tagger

5. Learning to Write Your Own Grammar

6. Writing a Probabilistic CFG

7. Writing a Recursive CFG

8. Using the Built-In Chunker

9. Writing Your Own Simple Chunker

10. Training a Chunker

11. Parsing Recursive Descent

12. Parsing Shift-Reduce

13. Parsing Dependency Grammar and Projective Dependency

14. Parsing a Chart

15. Using Inbuilt NERs

16. Creating, Inversing, and Using Dictionaries

17. Choosing the Feature Set

18. Segmenting Sentences Using Classification

19. Writing a POS Tagger with Context

20. Creating an NLP Pipeline

21. Solving the Text Similarity Problem

22. Resolving Anaphora

23. Disambiguating Word Sense

24. Performing Sentiment Analysis

25. Exploring Advanced Sentiment Analysis

26. Creating a Conversational Assistant or Chatbot

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تولید کننده: Udemy-Training