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Let’s Talk VDML | KJR Podcast Series

Let's Talk VDML Podcast Series - Trust your AI !

The KJR VDML podcast series aims to provide insights and practical guidance for developing robust and reliable Machine Learning (ML) models to deliver AI solutions. The podcasts explore real-world examples and the challenges associated with bias, error rates, and performance measurement in ML models.

VDML (Validation Driven Machine Learning) is a methodology developed by KJR to guide the development of robust and reliable ML models. 

By listening to the VDML podcasts, you will: 

The podcasts explore the concepts of VDML, including a test-first approach to machine learning, understanding the context of deploying AI applications, and the importance of validation, optimisation, integration, and governance in machine learning projects.

The podcasts delve into the potential risks and limitations associated with machine learning and AI. They discuss the lessons learned from past experiences and highlight the importance of identifying risks and understanding the limitations of ML models.

The podcasts feature guest speakers and case studies that provide practical examples of applying VDML in real-world scenarios. These insights can help you understand how VDML has been used in different contexts and industries.

The podcasts discuss techniques and strategies for validating, optimising, and resolving limitations in ML models. By implementing the recommendations shared in the podcasts, you can enhance the performance of your ML models and ensure they meet the desired objectives. 

You will learn valuable knowledge and insights into the best practices, challenges, and benefits of using VDML in ML projects. It can help you make informed decisions and improve the effectiveness and reliability of your AI applications.

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