9. Natural Language Processing (NLP)

Sections

Navigate through the learning materials and practice exercises.

1. 9

   Natural Language Processing (Nlp)

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   Natural Language Processing (NLP) enhances interactions between computers...

2. 9.1

   Understanding Natural Language Processing

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   Natural Language Processing (NLP) focuses on enabling machines to understand...

3. 9.2

   Types Of Nlp Tasks

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   In this section, we explore various Natural Language Processing (NLP) tasks...

4. 9.2.1

   Text Preprocessing

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   Text preprocessing is an essential step in Natural Language Processing that...

5. 9.2.2

   Text Classification

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   Text classification is a crucial Natural Language Processing (NLP) task that...

6. 9.2.3

   Named Entity Recognition (Ner)

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   Named Entity Recognition (NER) is a key NLP task that involves identifying...

7. 9.2.4

   Machine Translation

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   Machine Translation is the process by which computer programs automatically...

8. 9.2.5

   Speech Recognition And Text-To-Speech

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   This section discusses the fundamentals of speech recognition and...

9. 9.3

   Nlp Pipeline

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   The NLP Pipeline outlines the essential steps involved in processing natural...

10. 9.4

    Feature Extraction Techniques

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    Feature extraction techniques transform text data into usable numerical...

11. 9.4.1

    Bag Of Words (Bow)

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    The Bag of Words (BoW) model is a simple and effective technique used in...

12. 9.4.2

    Term Frequency – Inverse Document Frequency (Tf-Idf)

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    TF-IDF is a numerical statistic that reflects the importance of a word in a...

13. 9.4.3

    Word Embeddings

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    Word embeddings are vector representations of words used in NLP to capture...

14. 9.5

    Nlp With Machine Learning

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    This section discusses various machine learning techniques applied to NLP...

15. 9.6

    Deep Learning In Nlp

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    Deep learning techniques, particularly RNNs, LSTMs, and Transformers, have...

16. 9.6.1

    Recurrent Neural Networks (Rnn)

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    Recurrent Neural Networks (RNN) are a type of neural network particularly...

17. 9.6.2

    Long Short-Term Memory (Lstm) & Gru

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    LSTM and GRU are advanced types of recurrent neural networks designed to...

18. 9.6.3

    Transformers

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    Transformers are a revolutionary deep learning architecture in Natural...

19. 9.7

    Modern Nlp Models

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    Modern NLP models, including BERT and GPT, represent a significant...

20. 9.7.1

    Bert (Bidirectional Encoder Representations From Transformers)

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    BERT is a groundbreaking NLP model that uses masked language modeling and...

21. 9.7.2

    Gpt (Generative Pre-Trained Transformer)

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    GPT is a generative model based on transformers that excels in language...

22. 9.7.3

    Other Popular Models

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    This section provides an overview of other notable models used in Natural...

23. 9.8

    Evaluation Metrics For Nlp

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    This section provides an overview of evaluation metrics used to assess the...

24. 9.9

    Tools And Libraries For Nlp

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    This section introduces essential tools and libraries used in Natural...

25. 9.10

    Real-World Applications

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    This section explores the diverse applications of Natural Language...