<ul data-eligibleForWebStory="true"><li>Maximum Likelihood Estimation (MLE) estimates model parameters from observed data likelihood.</li><li>Gradient Descent optimizes functions by adjusting parameters in the direction of gradients.</li><li>Normal Distribution models symmetrically clustered data values around the mean in statistics.</li><li>Sigmoid function maps inputs to values between 0 and 1 in neural networks.</li><li>Cosine Similarity measures similarity between vectors in text analysis and recommendations.</li></ul>

25 Essential Mathematical Concepts for Data Science

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