The learning radius determines the number of neurons to be updated around the winning neuron. Any neuron that is in the circle of the radius will be updated during the learning process. The closer the neuron, the more updates that are happening. The farther away, the fewer.
- Title Page
- Copyright and Credits
- Packt Upsell
- Contributors
- Preface
- Machine Learning Basics
- Introduction to machine learning
- Data mining
- Artificial Intelligence
- Bio-AI
- Deep learning
- Probability and statistics
- Approaching your machine learning project
- Iris dataset
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Build, buy, or open source
- Additional reading
- Summary
- References
- ReflectInsight – Real-Time Monitoring
- Bayes Intuition – Solving the Hit and Run Mystery and Performing Data Analysis
- Risk versus Reward – Reinforcement Learning
- Fuzzy Logic – Navigating the Obstacle Course
- Color Blending – Self-Organizing Maps and Elastic Neural Networks
- Facial and Motion Detection – Imaging Filters
- Encyclopedias and Neurons – Traveling Salesman Problem
- Should I Take the Job – Decision Trees in Action
- Deep Belief – Deep Networks and Dreaming
- Microbenchmarking and Activation Functions
- Intuitive Deep Learning in C# .NET
- Quantum Computing – The Future
Learning radius
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