How to manage model and data versions

Managing data versions and model versions is critical in deploying machine learning models. This is because if you want to re-create the models or go back to fix them, you will need both the data that went into training the model and as well as the model hyperparameters itself.

In this video I explained that concept.
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Here's what I can do to help you. I speak on the topics of architecture and AI, help you integrate AI into your organization, educate your team on what AI can or cannot do, and make things simple enough that you can take action from your new knowledge.

I work with your organization to understand the nuances and challenges that you face, and together we can understand, frame, analyze, and address challenges in a systematic way so you see improvement in your overall business, is aligned with your strategy, and most importantly, you and your organization can incrementally change to transform and thrive in the future.

[krushnsonani]

I am very much impressed by your presentation. It is a direct point to point with simple graphics. I would like to request you to share the information about which application or software you are using for making your videos?

[soumyajitmukherjee]

how about if u have model in .pt, .onnx, format, which can go to a range of 1GB or more. I can place them in Teams folder or Cloud Drive. Is there any other options?