AI Researcher Needed - ML Model Comparison Project
Budget: £250 – £750 GBP
I need an experienced AI researcher to debug and validate my existing code that compares the effectiveness of Isolation Forest and LSTM for anomaly detection, specifically with time-series anomalies. The focus will be on their combined performance improvement.
Key Responsibilities:
- Debug the codebase that tests the two models and evaluates their combined approach.
- Validate the results that show individual model metrics, combined model improvements, statistical significance and performance comparisons.
Required Skills:
- Strong Python and ML debugging experience.
- Familiarity with Isolation Forest and LSTM.
- Experience with performance metrics, particularly Accuracy and F1 Score.
- Statistical analysis capability.
Key Focus:
- Confirm that combining these models yields measurable improvements over using the individual models.
Please note that the code is already implemented, and the role will primarily involve debugging and validating the results. I will provide a working codebase and expect a results validation report at the end of the project.
Must be available immediately for this 2-day remote project, with a budget of £200.
Key Responsibilities:
- Debug the codebase that tests the two models and evaluates their combined approach.
- Validate the results that show individual model metrics, combined model improvements, statistical significance and performance comparisons.
Required Skills:
- Strong Python and ML debugging experience.
- Familiarity with Isolation Forest and LSTM.
- Experience with performance metrics, particularly Accuracy and F1 Score.
- Statistical analysis capability.
Key Focus:
- Confirm that combining these models yields measurable improvements over using the individual models.
Please note that the code is already implemented, and the role will primarily involve debugging and validating the results. I will provide a working codebase and expect a results validation report at the end of the project.
Must be available immediately for this 2-day remote project, with a budget of £200.