CS5720 - Practical NLP Project Implementation

Building a Sentiment Analysis System

Let's implement a complete NLP project from scratch: a sentiment analysis system that can classify movie reviews as positive or negative using modern deep learning techniques.

Project Setup & Data

Set up environment, load IMDB dataset, and explore the data

pip install transformers torch datasets

Data Preprocessing

Clean text, tokenize with BERT tokenizer, and prepare data loaders

tokenizer = AutoTokenizer.from_pretrained('bert-base')

Model Architecture

Load pre-trained BERT and add classification head

model = AutoModelForSequenceClassification(...)

Training Pipeline

Set up training loop with proper optimization and evaluation

trainer = Trainer(model, args, train_dataset)

Evaluation & Testing

Evaluate model performance and analyze errors

accuracy = evaluate(model, test_loader)

Deployment

Create API endpoint and deploy to production

app = FastAPI(); @app.post("/predict")

Practical NLP Project Implementation

Building a Sentiment Analysis System

Project Setup & Data

Data Preprocessing

Model Architecture

Training Pipeline

Evaluation & Testing

Deployment

Project Resources

Try the Live Demo!

Practical NLP Project Implementation

Building a Sentiment Analysis System

Project Setup & Data

Data Preprocessing

Model Architecture

Training Pipeline

Evaluation & Testing

Deployment

Project Resources

Try the Live Demo!

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