Probability for Machine Learning & Deep Learning | Complete Intuitive Tutorial

Описание: In this video, we provide a complete and intuitive explanation of Probability in Machine Learning & Deep Learning. This lecture is designed for beginners, university students, and AI practitioners who want to build strong foundations in probability theory for ML and AI.

🔹 Topics Covered

Random Variables & Sample Space
Probability Distributions
Probability Mass Function (PMF)
Probability Density Function (PDF)
Cumulative Distribution Function (CDF)
Frequentist vs Bayesian Probability
Bayes’ Theorem (with real-world examples)
Bayesian Inference
Expectation, Variance & Covariance
Correlation & Statistical Independence
Sample Mean & Sample Variance
Naive Bayes Classifier
Similarity Measures (Cosine, Jaccard, Pearson)

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