Improve a Machine Learning Model for Text Classification
Budget: $15 – $25 USD
I have a Machine Learning project developed in Python using a Random Forest for text classification into 6 categories. Currently, the model achieves 70% accuracy, and I am looking for a Machine Learning expert to improve this accuracy to at least 85%.
Dataset:
9900 available data points for training.
400 reserved data points for testing (non-shareable, but available to test the quality of the delivered model).
Current Status:
The model is already developed and functioning in Python.
The code (both the model generator and the file that consumes the model and returns the category) is hosted on GitHub.
The model is deployed on Heroku and can be consumed via a Rest API (already configured).
Freelancer Requirements:
Proven experience in improving text classification models using Random Forest or advanced Machine Learning algorithms.
Familiarity with development tools in Python, API integration, and deployment platforms such as Heroku.
Ability to optimize the model and fine-tune hyperparameters to improve accuracy or suggest model architecture changes if necessary.
The deliverable must be an improved model that works with the existing API without requiring changes to the consumption structure.
Deliverables:
An optimized model that achieves at least 85% accuracy.
A report detailing the changes made and improvements implemented.
Assistance in testing the model with the reserved test data to ensure it maintains the expected classification accuracy.
Additional Notes:
The project is already functional; the focus is solely on optimizing the performance of the existing model.
Any changes to the model must integrate easily with the already configured Rest API.
Looking forward to your proposals. If you have experience in improving text classification models and deploying them on Heroku, this project is a great fit for you.
Dataset:
9900 available data points for training.
400 reserved data points for testing (non-shareable, but available to test the quality of the delivered model).
Current Status:
The model is already developed and functioning in Python.
The code (both the model generator and the file that consumes the model and returns the category) is hosted on GitHub.
The model is deployed on Heroku and can be consumed via a Rest API (already configured).
Freelancer Requirements:
Proven experience in improving text classification models using Random Forest or advanced Machine Learning algorithms.
Familiarity with development tools in Python, API integration, and deployment platforms such as Heroku.
Ability to optimize the model and fine-tune hyperparameters to improve accuracy or suggest model architecture changes if necessary.
The deliverable must be an improved model that works with the existing API without requiring changes to the consumption structure.
Deliverables:
An optimized model that achieves at least 85% accuracy.
A report detailing the changes made and improvements implemented.
Assistance in testing the model with the reserved test data to ensure it maintains the expected classification accuracy.
Additional Notes:
The project is already functional; the focus is solely on optimizing the performance of the existing model.
Any changes to the model must integrate easily with the already configured Rest API.
Looking forward to your proposals. If you have experience in improving text classification models and deploying them on Heroku, this project is a great fit for you.