Mini projects for MLOps
Setting up an environment for real-time product category classification.
Establishing a pipeline for real-time API serving of NLP models and monitoring usage based on authentication for enhancing efficiency in e-commerce.
Constructing a pipeline for conducting financial anomaly detection.
Setting up an environment for effectively monitoring and enhancing performance of the financial anomaly detection pipeline.
Exploring the ML cycle and optimizing models using MLFlow based on bank marketing data.
Hands-on practice of understanding, registering, and deploying models using credit approval data in the ML cycle.
Establishing a container-native learning environment for named entity recognition utilized in chatbots.
Utilizing Triton Inference Server for high-performance model serving across multiple ML/DL frameworks.
Building a pipeline for continuous model evaluation, retraining, and model updates in the manufacturing anomaly detection domain.
Setting up an independent Airflow environment for ML experimentation models.