Amir Farzad is a Machine Learning Engineer and Head of AI with a decade of experience building production-ready forecasting, anomaly detection, and NLP systems across industrial and enterprise domains. He combines academic rigor from a PhD program with hands-on engineering—delivering hybrid ML/Deep Learning solutions using Keras, TensorFlow, PyTorch and scikit-learn that have outperformed conventional methods on log and time-series data. At Clay he leads AI efforts, and previously drove high-impact projects at Pani Energy and the University of Victoria, including novel Auto-LSTM/Auto-GRU architectures and SeqGAN-based oversampling for imbalanced logs. He has a track record of turning research prototypes into reliable tools for hundreds of signals, optimizing pipelines for scale and speed while working closely with engineering and product teams. Based in Canada, Amir blends deep model development with practical deployment know-how and a persistent curiosity for new approaches in ML research.
Classification on the Google Cloud using Keras-Flask-MLP
Contributions:11 PRs, 3 pushes, 1 branch in 2 years 5 months
classificationflaskgoogle-cloudkerasmlp
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