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The Importance of Model Versioning In Machine Learning. - Unbox.ai

Version control is an essential concept in software development. Version control tools, such as Git, are used to manage and track source codes. Developers and organizations alike value source code because it is the backbone of their product(s), from which they earn revenue. Model versioning is the application of version control concepts within the machine learning process.

Machine learning and artificial intelligence offer an edge to businesses and developers over their competitors, motivating the competition to push to build the best model as it provides a business advantage. As developers optimize for speed and accuracy, minimizing errors also becomes a priority. Model versioning is a great tool for all of those purposes.

In this article, you will learn more about the importance of model versioning in machine learning by exploring a demo on how to apply it when building ML models and reviewing best practices to follow, limitations to be aware of, and some of the best tools currently available.

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Understanding NFTs - Part One

Non-fungible Tokens(NFTs) are tokens on the blockchain, representing a unique asset such as a piece of art. The blockchain is a digital ledger that stores transactions and can hold information. A major difference between the blockchain and traditional financial systems is that records stored on the blockchain are immutable, meaning they cannot be changed.

The current expression of NFTs in the real world is digital arts, but they can and will apply to anything digital: music, writing, video game items, and more. ' NFTs are important because they help verify ownership and prove the authenticity of digital items. On the internet today, users can copy digital items online and claim the ownership with no way to verify the claim. NFTs can provide a solution to that, due to their unique structure.

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