4 machine learning training paradigms, explained visually: - Transfer Learning - Fine-tuning - Multi-task Learning - Federated Learning

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• Programming runs on math • Logic comes from math • Algorithms depend on math • Data structures use math • AI models are built with math • Machine learning uses math • Deep learning relies on math • Linear algebra powers math-heavy systems • Probability drives decisions

- Programming sits on maths. - Algorithms run on maths. - Every AI model is maths. - Machine learning is maths. - Deep learning is maths. - Graphics are maths. - Simulations are maths. - Cryptography is maths. - Blockchain is maths. - Data science is maths. - Optimization is

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• Programming is built on math •Formal logic is a branch of math •Algorithm complexity is pure math •Data structures rely on discrete math •AI is applied calculus and linear algebra •Machine learning is statistical inference •Deep learning is gradient descent and matrix

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