AI-Powered Text Classification API (NLP-Based MVP)
Budget: $30 – $250 USD
I am looking for an experienced AI & NLP developer to build a small, focused text classification system powered by machine learning.
The goal of this project is to create an API-based NLP solution that receives text input and returns a classification result (such as sentiment, topic, or intent).
This is a well-scoped MVP project, designed to validate functionality without unnecessary complexity.
No datasets, models, or initial code will be provided. The freelancer is expected to design the solution from scratch using best practices and lightweight, efficient approaches.
Scope of Work:
AI / NLP Component:
Select an appropriate NLP approach (pretrained transformer or lightweight ML model)
Implement text preprocessing (tokenization, normalization)
Train or configure a single-label text classification model
Focus on accuracy, clarity, and maintainability (not large-scale optimization)
Backend & API Development:
Develop a RESTful API using FastAPI or Flask
Implement a prediction endpoint:
Accept text input
Return classification result in JSON format
Handle basic input validation and error responses
Testing & Documentation
Test the API with sample text inputs
Provide example requests and responses
Add short setup and usage instructions
Deliverables:
NLP model (trained or configured)
Python source code for the API
Sample input/output examples
Basic documentation for running the project locally
The goal of this project is to create an API-based NLP solution that receives text input and returns a classification result (such as sentiment, topic, or intent).
This is a well-scoped MVP project, designed to validate functionality without unnecessary complexity.
No datasets, models, or initial code will be provided. The freelancer is expected to design the solution from scratch using best practices and lightweight, efficient approaches.
Scope of Work:
AI / NLP Component:
Select an appropriate NLP approach (pretrained transformer or lightweight ML model)
Implement text preprocessing (tokenization, normalization)
Train or configure a single-label text classification model
Focus on accuracy, clarity, and maintainability (not large-scale optimization)
Backend & API Development:
Develop a RESTful API using FastAPI or Flask
Implement a prediction endpoint:
Accept text input
Return classification result in JSON format
Handle basic input validation and error responses
Testing & Documentation
Test the API with sample text inputs
Provide example requests and responses
Add short setup and usage instructions
Deliverables:
NLP model (trained or configured)
Python source code for the API
Sample input/output examples
Basic documentation for running the project locally
Related categories:
Python
Machine Learning (ML)
JSON
Full Stack Development
Flask
RESTful API
NLP
FastAPI
AI Model Development
Transformer Model