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  • deeplearning.ai
    • Neural Networks and Deep Learning
      • Wk2 - Python Basics with Numpy
      • Wk2 - Logistic Regression with a Neural Network mindset
      • Wk3 - Planar data classification with a hidden layer
      • Wk4 - Building your Deep Neural Network: Step by Step
      • Wk4 - Deep Neural Network - Application
    • Hyperparameter Tuning, Regularization and Optimization
      • Wk1 - Initialization
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    • Structuring Machine Learning Projects
    • Convolutional Neural Networks
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  • Neuroscience Paper
    • Rotation and Head Direction
    • Computational Models of Memory Search
    • Bayesian Delta-Rule Model Explains the Dynamics of Belief Updating
    • Sensory uncertainty and spatial decisions
    • A Neural Implementation of the Kalman Filter
    • Place cells, spatial maps and the population code for memory (Hopfield)
    • Spatial Cognitive Map
    • Event Perception and Memory
    • Interplay of Hippocampus and Prefrontal Cortex in Memory
    • The Molecular and Systems Biology of Memory
    • Reconsidering the Evidence for Learning in Single Cells
    • Single Cortical Neurons as Deep Artificial Neural Networks
    • Magnetic resonance-based eye tracking using deep neural networks
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  1. Hyperparameter tuning
  2. Regularization

Data augmentation

CV: when have small dataset, distort the image to increase training sample

PreviousDropout regularizationNextEarly stopping

Last updated 3 years ago

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