Sentiment Analysis Model Development
Budget: $10 – $30 USD
I need a robust data-analysis model that can read raw text and reliably detect the underlying sentiment (positive, negative, neutral). The scope is entirely focused on text data so I’m looking for someone comfortable with modern NLP workflows in Python—think spaCy, NLTK, scikit-learn, or a lightweight TensorFlow/PyTorch setup if you prefer deep-learning.
The workflow I have in mind is straightforward: you will start by cleaning and tokenising the texts, engineer any features you deem useful, build and validate the sentiment classifier, then package the finished model with clear usage instructions so I can feed it new text and retrieve the polarity score in one call. Accuracy matters more to me than fancy dashboards, but I do expect a concise README and a notebook or script that reproduces your results end-to-end.
Deliverables
• Well-commented training script or notebook
• Trained sentiment analysis model (serialised)
• README explaining setup, retraining, and inference steps
• Brief validation report showing metrics on a held-out test set (precision, recall, F1)
Please factor in the possibility of small iterations once I test the model on my own samples. If you’ve built text-classification or sentiment pipelines before, this should feel familiar—I’m eager to see your proposal.
The workflow I have in mind is straightforward: you will start by cleaning and tokenising the texts, engineer any features you deem useful, build and validate the sentiment classifier, then package the finished model with clear usage instructions so I can feed it new text and retrieve the polarity score in one call. Accuracy matters more to me than fancy dashboards, but I do expect a concise README and a notebook or script that reproduces your results end-to-end.
Deliverables
• Well-commented training script or notebook
• Trained sentiment analysis model (serialised)
• README explaining setup, retraining, and inference steps
• Brief validation report showing metrics on a held-out test set (precision, recall, F1)
Please factor in the possibility of small iterations once I test the model on my own samples. If you’ve built text-classification or sentiment pipelines before, this should feel familiar—I’m eager to see your proposal.