Calculus for ML & Data Science

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

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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