NLP-In-Python

🧠 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

• GitHub: VYaswanthKumar
• Email: vyaswanthkumar7@gmail.com
• Portfolio: vyaswanthkumar.github.io/Portfolio.in

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