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🧠 NLP-In-Python

A curated collection of Natural Language Processing (NLP) experiments, mini-projects, and scripts built using Python.

📖 Project Overview

This repository explores core NLP concepts with hands-on Python implementations. Each folder/script demonstrates techniques such as tokenization, stemming, lemmatization, text classification, sentiment analysis, topic modeling, and more.

🛠️ Tech Stack & Tools

  • Python 3.x

  • NLTK, spaCy, Scikit-Learn, Gensim

  • Pandas, NumPy for data handling

  • Matplotlib / Seaborn for visualizations

  • Jupyter Notebooks & .py scripts

📂 What’s Inside

Module / Folder Description
tokenization/ Scripts demonstrating word & sentence tokenization
preprocessing/ Cleaning text: stopwords, lowercasing, special chars
stemming_lemmatization/ Comparing stemming vs lemmatization techniques
sentiment_analysis/ Sentiment classifiers on sample datasets
topic_modeling/ LDA, NMF topic models on text corpora
text_classification/ Building and evaluating classifiers (Naive Bayes, SVM, etc.)
notebooks/ Interactive Jupyter notebooks showing experiments with explanations
data/ Sample text datasets (public domain or small samples)

(Actual folder names may vary — adapt as needed.)

✅ Key Features & Highlights

  • Clear and modular code structure — easy to navigate

  • Notebook + script versions — for both exploration & deployment

  • Visualization of word frequencies, topic distributions, etc.

  • Comparative study of multiple algorithms

  • Well documented — each notebook/script explains why & how

🚀 Why This Project Matters

  • Demonstrates your hands-on experience with fundamental NLP techniques

  • Shows your ability to choose, implement, compare, and explain models

  • A solid portfolio piece for ML / NLP roles

  • Useful foundation for building chatbots, summarizers, sentiment engines

🧩 Use Cases / Possible Extensions

  • Sentiment analysis for social media / product reviews

  • Topic modeling for document corpus (news, blogs)

  • Text classification (spam detection, news categorization)

  • Named Entity Recognition (NER) extension

  • Deploying as REST API using Flask / FastAPI

🧑‍💻 How to Run

  1. Clone the repo:

    git clone https://github.com/VYaswanthKumar/NLP-In-Python.git
cd NLP-In-Python

  2. Install dependencies (suggested virtual environment):

    pip install -r requirements.txt

  3. Run notebooks (e.g. jupyter notebook) or run specific scripts:

    python sentiment_analysis/sentiment_classifier.py

  4. View results / plots / outputs within notebooks or output files.

💡 Why You Should Review This

As a recruiter or technical lead, here’s why this project is relevant:

  • You see structured, modular, well-documented code

  • You observe understanding of NLP fundamentals + tools

  • You can assess algorithm choices, evaluation metrics, trade-offs

  • It hints at my ability to extend the project, push it further

📬 Contact & Next Steps

Feel free to explore this repo, run experiments, or reach out to discuss improvements or contributions!