About this Course

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Beginner Level

Basic familiarity with functions, basic algebra, and Python will help you get the most out of this specialization.

Approx. 25 hours to complete
English

What you will learn

  • Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients

  • Approximately optimize different types of functions commonly used in machine learning

  • Visually interpret differentiation of different types of functions commonly used in machine learning

  • Perform gradient descent in neural networks with different activation and cost functions

Skills you will gain

  • Calculus
  • Mathematical Optimization
  • Gradient Descent
  • Machine Learning
  • Newton'S Method
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level

Basic familiarity with functions, basic algebra, and Python will help you get the most out of this specialization.

Approx. 25 hours to complete
English

Offered by

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DeepLearning.AI

Syllabus - What you will learn from this course

Week
1
Week 1
9 hours to complete

Week 1 - Derivatives and Optimization

9 hours to complete
28 videos (Total 113 min), 3 readings, 4 quizzes
Week
2
Week 2
7 hours to complete

Week 2 - Gradients and Gradient Descent

7 hours to complete
14 videos (Total 51 min)
Week
3
Week 3
9 hours to complete

Week 3 - Optimization in Neural Networks and Newton's Method

9 hours to complete
17 videos (Total 91 min), 2 readings, 3 quizzes

About the Mathematics for Machine Learning and Data Science Specialization

Mathematics for Machine Learning and Data Science

Frequently Asked Questions

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