Advanced Metrics Data Science Notebook
Budget: ₹1,500 – ₹12,500 INR
I'm looking for a seasoned data scientist, with expert knowledge in scikit-learn, matplotlib, and jupyter notebooks. The primary goal is to develop a powerful notebook capable of calculating a range of metrics-- not only accuracy, precision, and recall, but also the ROC-AUC, Silhouette score, Davies-Bouldin Index, Calinski-Harabasz Index, Adjusted Rand Index, and Normalized Mutual Information from isolation forest models.
The specifics I'm after include:
- Developing a jupyter notebook (Python)
- Utilizing the existing isolation forest models for outlier detection
- Calculating metrics like ROC-AUC, Silhouette score, Davies-Bouldin Index, etc.
In addition to this, the notebook should present the results visually through scatter plots, confusion matrices, and histograms. Experience in data visualizations and clarity in presenting statistical data is key. This project requires a good grasp of statistical methodologies and proficiency in pycaret and scikit-learn for flawless execution.
The specifics I'm after include:
- Developing a jupyter notebook (Python)
- Utilizing the existing isolation forest models for outlier detection
- Calculating metrics like ROC-AUC, Silhouette score, Davies-Bouldin Index, etc.
In addition to this, the notebook should present the results visually through scatter plots, confusion matrices, and histograms. Experience in data visualizations and clarity in presenting statistical data is key. This project requires a good grasp of statistical methodologies and proficiency in pycaret and scikit-learn for flawless execution.