Natural Language Processing (NLP) enables computers to process, understand and generate human language. Working on NLP projects helps you gain practical experience in tasks such as sentiment analysis, text classification, chatbots, language translation and speech recognition.
1. Sentiment Analysis & Emotion Detection
Sentiment analysis projects classify text as positive, negative or neutral while emotion detection projects identify emotions expressed through language.
- Twitter Sentiment Analysis
- Sentiment Analysis with a Recurrent Neural Network (RNN)
- Sentiment Classification Using BERT
- NLP Sentiment Analysis for US Election
- Sentiment Analysis using NLTK
2. Spam Detection
These projects classify text into predefined categories to identify unwanted messages, misinformation and other types of content.
3. Chatbots & Intent Recognition
Chatbot projects process user messages to identify intents and generate appropriate responses for conversational applications.
4. Text Processing & Information Extraction
These projects process unstructured text to extract structured information, identify language, detect similarities and discover topics.
- Plagiarism Detection
- Resume Parser
- Language Detection
- Named Entity Recognition Using NLTK and spaCy
- Topic Modeling Using Latent Dirichlet Allocation (LDA)
- Topic Modeling with NLTK
- Autocorrector Feature Using NLP
5. E-commerce & Product Review Analysis
These projects use NLP to analyze customer reviews, identify opinions about products and extract useful insights from e-commerce feedback.
6. Text Generation & Language Modeling
These projects use language models and deep learning to predict words, complete sentences and generate text.
- Text Generation using FNet
- Next Word Prediction
- Sentence Autocomplete Using PyTorch
- Sentence Autocomplete Using TensorFlow
- Next Sentence Prediction using BERT
7. Text Summarization & Machine Translation
These projects use NLP models to shorten documents while retaining important information or translate text between different languages.
8. Speech Recognition & Speech Processing
These projects convert spoken language into text or transform written text into speech. They are particularly useful for transcription, accessibility and voice-based applications.
