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Learn how to fine-tune language models using Apple MLX, exploring model sizes, data diversity, and optimization techniques. This guide covers the process from basic fine-tuning to creating chat models.
Learn how to fine-tune language models for memorization of custom datasets. This guide covers data preparation, hyperparameter selection, and practical implementation steps.
An in-depth exploration of data science, covering key concepts in data analytics, artificial intelligence, and machine learning. Learn about career opportunities and skills needed to succeed in this rapidly growing field.
Explore common misconceptions in data analysis and learn how to avoid statistical traps. This article examines real-world examples of data misinterpretation and their consequences.
Explore the probabilistic foundations of linear regression in machine learning. Learn how assumptions about noise and priors lead to least squares and regularization techniques.
Explore the probabilistic foundations of linear regression in machine learning. Discover how assumptions about noise and priors lead to least squares and regularization techniques.
Explore how variational inference enables AI systems and brains to build efficient models from incomplete data. Learn about the evidence lower bound (ELBO) and its role in modern intelligent systems.
Explore the fundamental concepts of probability distributions and their crucial role in AI and machine learning. Learn how entropy, cross-entropy, and KL divergence shape modern algorithms.
Explore the fundamental algorithm behind machine learning systems like GPT and AlphaFold. Learn how backpropagation enables artificial neural networks to learn and why it differs from biological brains.