Getting ready for Phase 2
Workshop
CompleteWelcome to Phase 2: Applying ML Techniques
The second phase of the AI ML Fellowship program focuses on the practical application and refinement of machine learning models.
Phase 2 breakdown
The core theme is the practical application, optimisation, and responsible deployment of machine learning models.
Main topics covered
Model Engineering and Training:
Developing, training, and optimising various ML model architectures and handling complex data.
Model Evaluation:
Rigorously assessing models, selecting metrics, and analysing bias-variance trade-offs.
Data Security, Privacy, and Governance:
Navigating compliance, implementing security measures, and fostering a security-conscious culture.
Hackathon:
Putting Phase 2 learning into real-world practice.
Exciting connections to your role
Improving decision-making accuracy:
Accurate and reliable ML-driven insights through model optimisation.
Developing adaptive systems:
Building models that adapt to changing data and environments.
Ensuring data integrity and compliance:
Applying techniques to protect sensitive data and mitigate risk.
Action item: Share what you want to learn in Phase 2
Directions: In the chat, share what you are most excited to learn or apply from this phase!