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Introduction to Probability for Computer Scientists` is designed to provide foundational knowledge in probability theory tailored specifically for computer science applications. The course focuses on how probability is used to solve problems related to algorithms, data analysis, machine learning, cryptography, and networking. It covers key probability concepts such as random variables, distributions, conditional probability, and … Read more

Stanford University’s Machine Learning course, taught by Professor Andrew Ng, is one of the most popular courses in the field of AI. It offers a comprehensive introduction to machine learning, data mining, and statistical pattern recognition. The course emphasizes both the theoretical foundations of machine learning and practical aspects, with real-world examples and hands-on exercises … Read more