Mastering the ML Lifecycle: Using MLflow for Traditional ML, Deep Learning and L

In this session, we will dive deep into the full lifecycle of traditional Machine Learning and Deep Learning workflows — from data preparation and model training to experiment tracking, model evaluation, and deployment strategies. Learn best practices for managing scalable ML pipelines, tracking experiments using tools like MLflow, and deploying models into production environments. We will cover key concepts such as model versioning, reproducibility, and deployment patterns for both ML and DL models. Whether you are building classification models, recommendation systems, or deep neural networks, this event will give you practical insights and hands-on techniques to streamline your workflows and deliver reliable AI solutions.

What You’ll Learn:

• Designing end-to-end ML & DL pipelines

• MLflow tracing for LLM observability

• Model training and hyperparameter tuning

• Experiment tracking with MLflow

• Model versioning and registry management

• Deployment strategies (batch, real-time, REST APIs)

• Tips for monitoring, scaling, and maintaining models in production

Agenda

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Speaker

Teodora Mladenovska - Pythian (Senior ML Engineer)

Host

Jasmina Dimitrievska

DevOps Engineer / Solutions Architect with +5 years of experience in application development, integration, automation, planning and designing system’s architecture for on-premises and cloud infrastructure. Leading project workflows with latest DevOps practices in the software industry. Engaging in public speaking activities to share knowledge and advocate for technological advancements.

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Partner

Base42 (https://base42.mk/)
What is Base42?
A place for builders, and the curious
Started with the idea that knowledge should be proliferated as much as possible, as often as possible and reach as many people as possible the goal of Base42 is to help enable people and encourage communities to be created, give them the tools to grow, get together and focus on achieving that goal, to build together, not alone.

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Complete your event RSVP here: https://gdg.community.dev/events/details/google-gdg-skopje-presents-mastering-the-ml-lifecycle-using-mlflow-for-traditional-ml-deep-learning-and-llms/.