10 NLP Projects For Beginners to Boost Resume


Why Build NLP Projects?

NLP projects help you gain practical skills. Show recruiters you can apply NLP concepts by building real-world projects.

1. Sentiment Analysis

Classifying text reviews as positive, negative, or neutral sentiment is an essential text classification skill in NLP. Performing sentiment analysis on datasets of product reviews, tweets, or movie reviews is a great beginner project.

2. Chatbot Development

Developing a chatbot from scratch is an excellent way to showcase NLP skills. You can build rule-based chatbots and also experiment with more advanced chatbots powered by seq-to-seq models and transformers.

3. Named Entity Recognition

Named entity recognition involves identifying and categorizing named entities like people, organizations, locations, etc in text data. Implementing NER on news articles or legal documents allows you to demonstrate proficiency in working with structured text.

4. Text Summarization

Text summarization involves generating concise summaries of long documents while preserving key information and overall meaning. Building this shows ability to process and comprehed large volumes of text data for key insights.

5. Language Translation

Language translation is a foundational NLP task. You can develop basic translation models like English to French and also explore advanced multilingual models using transformers like GPT-3. This demonstrates core translation abilities.

6. Text Generation

Text generation allows creating original text like stories, poems, lyrics etc. You can leverage RNNs and language models like GPT-2. It enables you to showcase creativity and writing abilities.

7. Speech Recognition

Developing speech to text transcription models leverages both audio data and NLP. You can build speech recognition models using DeepSpeech, Google Speech API etc. This highlights proficiency in both speech and text processing.

8. Question Answering

Question answering involves building systems that can extract answers from a knowledge base or context document. You can use BERT and other models. It demonstrates reading comprehension skills.

9. Topic Modeling

Topic modeling using LDA and NMF helps uncover hidden semantic structures and topics within text. Implementing topic models on news and research papers highlights text analysis abilities.

10. Fake News Detection

Developing models to detect fake news and misinformation is hugely relevant today. You can classify articles as real or fake using datasets. This demonstrates commitment to tackling real-world problems with NLP.

Boost Your NLP Skills!

Hands-on projects combined with online NLP courses provide job-ready skills. Use libraries like NLTK, TensorFlow and supplement with tutorials.