When creating a new model it’s crucial that it is not only accurate and efficient, but also secure and easily manageable for deployment and inference testing. Join us for an in-depth webinar where you will learn how to build a robust ML model from scratch with a strong emphasis on security and scalability.

Whether you’re just starting your journey as a Data Scientist or ML Engineer, or you’re looking to refine your skills in secure model development and deployment, this webinar will equip you with the knowledge and practical skills to succeed. This session will help ensure your models are built on a secure foundation from the ground up.

Key Takeaways

• Best practices in developing machine learning models starting from writing the first line of code to a fully deployed model
• Techniques to ensure security of your model that don’t disrupt your workflow
• How to make a model ready for management in JFrog ML