Tag: Data Science
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GIGO – Garbage In, Garbage Out
The principle “Garbage In, Garbage Out” (GIGO) asserts the essential link between input data quality and output reliability, emphasizing the need for careful data validation. Rooted in computing history, its relevance spans across fields, advocating for meticulous data handling to ensure accurate outcomes.
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LLM – Large Language Model
Large Language Models (LLMs) are sophisticated AI systems designed for language processing. They learn from vast text datasets, excelling in tasks like translation and content creation, and continuously evolve based on new data and user interactions.
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Causal Inference
Causal inference provides a framework for deducing the relationship between cause and effect using empirical data. It employs a variety of rigorous methods to ensure the validity of its findings, making it indispensable in fields such as policy evaluation, economics, and healthcare.
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Attention is All You Need Whitepaper
“Attention is All You Need” is a groundbreaking whitepaper that introduces the Transformer model in natural language processing. The model relies on a self-attention mechanism and an encoder-decoder architecture, eschewing traditional recurrent and convolutional networks. Despite its simplicity, it achieved superior results in machine translation tasks.