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Calculus for ML & Data Science

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Optimize and interpret machine learning functions using gradients, derivatives, and gradient descent in neural networks.

Key AI Functions:Calculus,Machine Learning,Newton's Method,Gradient Descent,Mathematical Optimization

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Description for Calculus for ML & Data Science

Features of Course

Utilize the properties of gradients and derivatives to analytically optimize various types of functions that are frequently employed in machine learning.

Approximately optimize various types of functions that are frequently employed in machine learning.

Visually interpret the differentiation of various types of functions that are frequently employed in machine learning.

Implement gradient descent in neural networks that utilize distinct activation and cost functions.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by DeepLearning.AI

Duration: 26 hours (approximately)

Schedule: Flexible

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