Free online courseCalculus for Machine Learning

Duration of the online course: 7 hours and 33 minutes

New course

Master calculus for machine learning with this comprehensive online course, covering key concepts like derivatives and integral calculus tailored for AI applications.

Course Description

Enhance your understanding of machine learning with this comprehensive online course focusing on calculus concepts tailored for artificial intelligence applications. Explore the foundational topics that underpin modern machine learning techniques, starting with Calculus I, where you'll delve into the key concept of limits, including practical exercises on calculating limits that are crucial for understanding how derivatives arise. The course progresses to Differential Calculus, a core component in machine learning, offering insights into derivative rules, power rules, and differentiation processes that help optimize algorithms.

Expand your knowledge with Automatic Differentiation, a pivotal topic for implementing efficient machine learning models, utilizing PyTorch and TensorFlow to streamline calculations. Transition seamlessly into Calculus II, focusing on partial derivatives. Engage in hands-on exercises designed to solidify your grasp of how partial derivatives function, particularly how they relate to gradient descent and optimizing cost functions such as mean squared error.

Integral calculus rounds out the course, presenting tools to master numeric integration and integral calculus rules, which play a crucial role in evaluating models using techniques like the ROC curve, an essential measure for binary classification tasks. This course offers a robust foundation in calculus tailored specifically for machine learning, equipping you with the skills needed to understand and apply mathematical concepts to real-world AI problems effectively.

Course content

  • Video class: Calculus I: Limits

    0h03m

  • Video class: Intro to Differential Calculus —Topic 42 of Machine Learning Foundations

    0h13m

  • Video class: Intro to Integral Calculus –Topic 43 of Machine Learning Foundations

    0h02m

  • Video class: The Method of Exhaustion – Topic 44 of Machine Learning Foundations

    0h06m

  • Video class: Calculus of the Infinitesimals – Topic 45 of Machine Learning Foundations

    0h10m

  • Video class: Calculus Applications – Topic 46 of Machine Learning Foundations

    0h08m

  • Video class: Calculating Limits – Topic 47 of Machine Learning Foundations

    0h18m

  • Video class: Exercises on Limits – Topic 48 of Machine Learning Foundations

    0h01m

  • Video class: Derivatives and Differentiation — Segment 2 of Subject 3, "Limits

    0h01m

  • Video class: The Delta Method – Topic 49 of Machine Learning Foundations

    0h15m

  • Video class: How Derivatives Arise from Limits – Topic 50 of Machine Learning Foundations

    0h14m

  • Video class: Derivative Notation — Topic 51 of Machine Learning Foundations

    0h04m

  • Video class: The Derivative of a Constant –Topic 52 of Machine Learning Foundations

    0h01m

  • Video class: The Power Rule for Derivatives – Topic 53 of Machine Learning Foundations

    0h01m

  • Video class: The Constant Multiple Rule for Derivatives — Topic 54 of Machine Learning Foundations

    0h03m

  • Video class: The Sum Rule for Derivatives — Topic 55 of Machine Learning Foundations

    0h02m

  • Video class: Exercises on Derivative Rules — Topic 56 of Machine Learning Foundations

    0h03m

  • Video class: The Product Rule for Derivatives — Topic 57 of Machine Learning Foundations

    0h03m

  • Video class: The Quotient Rule for Derivatives — Topic 58 of Machine Learning Foundations

    0h04m

  • Video class: The Chain Rule for Derivatives — Topic 59 of Machine Learning Foundations

    0h06m

This free course includes:

7 hours and 33 minutes of online video course

Exercises to train your knowledge

Certificate of course completion

100% free, from content to certificate

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