variational autoencoder Anomaly Detection using TensorFlow
Budget: €20 – €60 EUR
For this project, I'm seeking a skilled machine learning engineer with proficiency using TensorFlow jupyter notebook to create a variational autoencoder model. Your task will be to detect anomalies related to mobility patterns within an Excel-format dataset.
Key Tasks Include:
- Analyzing a large dataset with more then am million rows and 32 columns.
- Building a variational autoencoder in TensorFlow specifically designed to identify anomalies in mobility patterns.
-Visualize the result between two time
Ideal skills and experience:
- Proficient in TensorFlow and machine learning algorithms.
- Experience with variational autoencoder .
- Demonstrable expertise in anomaly detection algorithms, particularly in mobility patterns data.
Key Tasks Include:
- Analyzing a large dataset with more then am million rows and 32 columns.
- Building a variational autoencoder in TensorFlow specifically designed to identify anomalies in mobility patterns.
-Visualize the result between two time
Ideal skills and experience:
- Proficient in TensorFlow and machine learning algorithms.
- Experience with variational autoencoder .
- Demonstrable expertise in anomaly detection algorithms, particularly in mobility patterns data.