Mastering Neural Networks Techniques
Explore advanced data techniques, learning rates, activation functions, cost functions, overfitting, and solutions for neural networks in this informative content. Enhance your understanding of Weight initialization, batching, backpropagation, and more to optimize your neural network model effectively.
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Presentation Transcript
Neural Networks Pt 2 Mihir Patel and Nikhil Sardana
Data Techniques Expanding datasets Weight initialization Narrow gaussian Batching
Learning Rate Step size for backpropagation
Activation Functions: tanh y = (ex-e-x)/(ex+ e-x) Benefits Greater derivative = faster learning -1 vs. 0 prevents stagnation
Cost Function: Cross-Entropy http://neuralnetworksanddeeplearning.com/chap3.html#saturation2_anchor Saturation Needs Approaches 0 when correct Always has positive sign Benefits Doesn t give 0 when incorrect
Overfitting Over-matching dataset
Solutions to Overfitting Weight Decay Punish larger weights Dropout
