Apr 22, 2025●12 reads●MIT License

Comprehensive NLP course: tokenization, embeddings, NER, and RNNs in Python

data-preprocessing
deep-learning
jupyter-notebook
machine-learning
natural-language-processing
nlp-course
nlp-projects
python
rnn
text-classification
tokenization
transformers
word-embeddings

r
Ratikanta Rout

Alt text

🌟 NLP-FULL-COURSE-REPO: A Complete Hands-on Guide to Natural Language Processing

Welcome to my complete NLP course repository! This project provides step-by-step Jupyter Notebooks covering all major Natural Language Processing concepts with practical examples using Python. Whether you're a beginner or an intermediate learner, this is your go-to resource for learning NLP the right way.

🔗 GitHub Repository: NLP-FULL-COURSE-REPO

🛠️ Tools & Technologies
Python, NLTK, SpaCy

Scikit-learn, TensorFlow, PyTorch

Hugging Face Transformers

Jupyter Notebooks

Google Colab

📚 What You'll Learn

Text Preprocessing (Tokenization, Lemmatization, Stopword Removal)
Feature Engineering (TF-IDF, Count Vectorization, Word Embeddings)
Text Classification (Logistic Regression, Naive Bayes, SVM)
Named Entity Recognition (NER)
Sentiment Analysis
RNN, LSTM, and BiLSTM Implementation
Transformer-based Models (BERT)
Semantic Similarity using Embeddings
Deployment-Ready NLP Pipelines

📁 Repository Structure

NLP-FULL-COURSE-REPO/
│
├── 1_Text_Preprocessing/
├── 2_Feature_Extraction/
├── 3_Classification_Models/
├── 4_Sequence_Models/
├── 5_BERT_Implementation/
├── 6_Sentiment_Analysis/
└── README.md