2025-08-11 –, Main Hall
Deploying machine learning models doesn’t have to feel like a leap into the unknown. This talk turns complex deployment processes into digestible steps, guiding you through containerization, serverless systems, and cloud platforms. With best practices for monitoring and scaling, attendees will gain the tools to transition confidently from experimentation to impactful production-ready models.
Transitioning ML models from development to production can be challenging. This talk demystifies the deployment process, offering a comprehensive guide to getting your models into production environments securely and efficiently. We'll explore various deployment strategies, including containers, serverless architectures, and dedicated ML platforms. Learn about best practices for monitoring, scaling, and maintaining your models post-deployment. By the end of this session, you'll be equipped with actionable insights and tools to deploy your models confidently and ensure they deliver real-world.
Ariane Djeupang is a Machine Learning Engineer and Project Manager, passionate about fostering community growth and innovation in the tech industry. She is dedicated to promoting diversity and inclusion, actively participating in the Python | Django | PyLadies communities and other initiatives that empower underrepresented groups in technology. Her commitment to mentorship and community