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This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.
With the evolution of Data Warehouses and Data Lakes, they have certainly become more specialized yet siloed in their respective landscapes over the last few years. Both data management technologies each have their own identities and are best used for certain tasks and needs, however they also struggle in providing some important abilities.
The models behind machine learning (ML) services are continuously being updated, and the new models are usually more accurate than the old ones. But an overall improvement in accuracy can still be accompanied by regression — a loss of accuracy — in particular cases.
By organizing information, databases are an essential component of nearly every computer program and online service. But the rigid structure of conventional database systems also constrains how they can be used. These systems require preset schemas and can only answer queries with well-defined semantics written in SQL (structured query language). Queries must be exacting to return correct information. Moreover, the data must be stored in a way to comply with the schema; therefore, taking advantage of the abundance of available unstructured data is challenging.
rclip is a command-line photo search tool based on the awesome OpenAI's CLIP neural network.