Merge pull request #1605 from yashksaini-coder/docs-1591

📝[Docs]: NLP guide

NLP/README.md

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+# NLP Naturla Language Processing
+
+Natural Language Processing (NLP) is a field of machine learning that focuses on the interaction between computers and humans through natural language. It involves teaching machines to understand, interpret, and generate human language in a way that is both meaningful and useful. NLP combines computational linguistics with statistical, machine learning, and deep learning models to process and analyze large amounts of natural language data.
+
+## Workflow Diagram
+
+```mermaid
+
+graph TD;
+    A[Start] --> B[Check NLTK Resources Availability];
+    B --> C[Load or Download SentenceTransformer Model];
+    C --> D[Read Input Text File];
+    D --> E[Extract Keywords from Text];
+    E --> F[Generate Text Summary];
+    F --> G[Display Results];
+    G --> H[End];
+```
+
+## Steps and Processes
+
+### 1. Ensure NLTK Resources are Available
+- The script ensures that necessary NLTK resources are downloaded and available for use.
+
+### 2. Load or Download SentenceTransformer Model
+- The script loads the SentenceTransformer model from a local directory or downloads it if not available.
+
+### 3. Read Input Text File
+- The script reads the input text file named `input.txt` from the current directory.
+
+### 4. Extract Keywords from Text
+- The script extracts the top N keywords from the given text using word frequency and importance scores.
+
+### 5. Generate Text Summary
+- The script summarizes the given text by selecting the top N most important sentences based on cosine similarity.
+
+### 6. Print Results
+- The script prints the extracted keywords and the generated summary.
+
+## Functions
+
+- **load_or_download_model()**: Loads the SentenceTransformer model from a local directory or downloads it if not available.
+- **download_nltk_resources()**: Ensures that necessary NLTK resources are downloaded and available.
+- **extract_keywords(text, model, top_n=10)**: Extracts the top N keywords from the given text using word frequency and importance scores.
+- **summarize_text(text, model, num_sentences=3)**: Summarizes the given text by selecting the top N most important sentences based on cosine similarity.
+- **main()**: Main function that ensures NLTK resources are available, loads the model, reads the input text file, extracts keywords, generates a summary, and prints the results.
+
+## Usage
+
+- Ensure that the input text file `input.txt` is present in the current directory.
+- Run the script to extract keywords and generate a summary of the text in `input.txt`.
+
+### Online Resources
+- **NLTK Documentation**: [NLTK Documentation](https://www.nltk.org/documentation.html) provides comprehensive information on how to use the NLTK library for various NLP tasks.
+- **SentenceTransformers Documentation**: [SentenceTransformers Documentation](https://www.sbert.net/docs/) offers detailed guides and examples on how to use the SentenceTransformers library for sentence embeddings and other NLP applications.
+- **Kaggle**: [Kaggle](https://www.kaggle.com/) is a platform for data science competitions and datasets, where you can find numerous NLP datasets and projects.
+- **Towards Data Science**: [Towards Data Science](https://towardsdatascience.com/) is a Medium publication with articles and tutorials on NLP and other data science topics.
+- **Hugging Face**: [Hugging Face](https://huggingface.co/) provides a wide range of NLP models and datasets, along with an active community and resources for learning and collaboration.
+
+### Libraries
+- **spaCy**: [spaCy](https://spacy.io/) is an open-source library for advanced NLP in Python, designed for production use.
+- **Gensim**: [Gensim](https://radimrehurek.com/gensim/) is a library for topic modeling and document similarity analysis.
+- **Transformers**: [Transformers](https://huggingface.co/transformers/) by Hugging Face is a library for state-of-the-art NLP models, including BERT, GPT-3, and more.
+- **TextBlob**: [TextBlob](https://textblob.readthedocs.io/en/dev/) is a simple library for processing textual data, providing a consistent API for diving into common NLP tasks.
+- **CoreNLP**: [CoreNLP](https://stanfordnlp.github.io/CoreNLP/) by Stanford NLP Group is a suite of NLP tools that provide various linguistic analysis tools.
+- **Flair**: [Flair](https://github.com/flairNLP/flair) is a simple framework for state-of-the-art NLP, developed by Zalando Research.
+
+These resources and libraries can help you further enhance your NLP projects and stay updated with the latest advancements in the field.