We may earn an affiliate commission when you visit our partners.

Backpropagation

Save
May 1, 2024 Updated May 12, 2025 30 minute read

Backpropagation, short for "backward propagation of errors," is a fundamental algorithm in the world of artificial intelligence (AI) and machine learning (ML). At its core, it is the method by which artificial neural networks, the very systems that power many modern AI applications, learn from data. Imagine a student learning a new skill; they make attempts, receive feedback on their errors, and adjust their approach for the next try. Backpropagation works in a conceptually similar way for neural networks. It efficiently calculates how much each internal parameter, or "weight," within the network contributed to any errors in its predictions. This information is then used to fine-tune these weights, gradually improving the network's performance over time.

Path to Backpropagation

Take the first step.
We've curated 24 courses to help you on your path to Backpropagation. Use these to develop your skills, build background knowledge, and put what you learn to practice.
Sorted from most relevant to least relevant:

Share

Help others find this page about Backpropagation: by sharing it with your friends and followers:

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Backpropagation.
This textbook provides a comprehensive overview of neural networks, including a detailed treatment of backpropagation. It is suitable for advanced learners and researchers with a strong background in mathematics and computer science.
This classic textbook provides a comprehensive overview of artificial neural networks, including an in-depth treatment of backpropagation. It is suitable for advanced learners and researchers.
This comprehensive textbook provides an in-depth exploration of deep learning, including a detailed chapter on backpropagation. It is suitable for advanced learners and researchers.
Provides a comprehensive overview of pattern recognition and machine learning, including a detailed discussion of backpropagation. It is suitable for advanced learners and researchers.
Provides a detailed treatment of neural networks for pattern recognition, including a discussion of backpropagation. It is suitable for advanced learners and researchers.
Provides a hands-on introduction to deep learning using Python, including a discussion of backpropagation. It is suitable for practitioners and those seeking a practical understanding of the topic.
Provides a practical guide to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It includes a discussion of backpropagation as part of neural network training.
Provides a probabilistic perspective on machine learning, including a discussion of backpropagation. It is suitable for advanced learners and researchers with a strong background in mathematics.
Provides an algorithmic perspective on machine learning, including a discussion of backpropagation. It is suitable for advanced learners and researchers with a strong background in mathematics and computer science.
Covers the theoretical foundations of neurocomputing, including a detailed discussion of backpropagation. It is suitable for advanced learners and researchers with a strong background in mathematics.
Provides a comprehensive overview of backpropagation, including its theoretical foundations and practical applications. It is suitable for advanced learners and researchers.
This introductory textbook provides a clear and accessible overview of neural networks, including an explanation of backpropagation. It is suitable for beginners and those seeking a gentle introduction to the topic.
Table of Contents
Our mission

OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.

Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.

Find this site helpful? Tell a friend about us.

Affiliate disclosure

We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.

Your purchases help us maintain our catalog and keep our servers humming without ads.

Thank you for supporting OpenCourser.

© 2016 - 2025 OpenCourser