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GitHub / suryanshyaknow / APS-fault-detection
based on the befitting sensors fetched data, prediction is to be made whether the failure in a vehicle is due to APS or some other component. Emphasis is on reducing the consequential cost by reducing the false positives and false negatives and more importantly false negatives as it appears cost incurred due to them is 50 times higher.
JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/suryanshyaknow%2FAPS-fault-detection
Stars: 0
Forks: 1
Open Issues: 0
License: mit
Language: Jupyter Notebook
Repo Size: 10.6 MB
Dependencies:
29
Created: over 1 year ago
Updated: over 1 year ago
Last pushed: over 1 year ago
Last synced: over 1 year ago
Topics: airflow, aws, ec2-instance, machine-learning, machine-learning-pipelines, machine-learning-project, python, sensors-data
Files
Dependencies
- actions/checkout v3 composite
- aws-actions/amazon-ecr-login v1 composite
- aws-actions/configure-aws-credentials v1 composite
- python 3.8 build
- Pillow *
- PyYAML *
- apache-airflow ==2.5.0
- apache-airflow-providers-common-sql ==1.3.1
- apache-airflow-providers-ftp ==3.2.0
- apache-airflow-providers-http ==4.1.0
- apache-airflow-providers-imap ==3.1.0
- apache-airflow-providers-sqlite ==3.3.1
- dill *
- imbalanced-learn *
- kneed *
- numpy *
- pandas *
- pathspec *
- pendulum *
- plotly *
- prettytable *
- pymongo *
- python-daemon *
- python-dateutil *
- python-dotenv *
- scikit-learn *
- scipy *
- seaborn *
- sklearn *