This course is divided into two parts. In the first part, you will be introduced to the concepts from probability theory and statistics with strong relevance in machine learning and data science. In the second part, you’ll explore gradient calculus and numerical optimization algorithms like gradient descent, stochastic gradient descent, etc.

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