Nilavukkarasan R

Architect focused on building simple, sustainable systems that scale. I work primarily with insurance and financial services organisations, translating ambitious goals into pragmatic architectures

Joined on Feb 14, 2026

Nilavukkarasan R

May 7

The Transformer: The Architecture Behind Modern AI

#gpt #transformer #llm #ai

5 min read

Nilavukkarasan R

Apr 19

Attention Mechanisms: Stop Compressing, Start Looking Back

#selfattention #ai #transformer #multiheadattention

4 min read

Nilavukkarasan R

Apr 13

Recurrent Neural Networks: Giving Networks Memory

#rnn #lstm #ai #deeplearning

5 min read

Nilavukkarasan R

Apr 11

Batch Normalization and Residual Connections: Going Deeper Without Breaking

#deeplearning #residualconnections #batchnormalization #cnn

4 min read

Nilavukkarasan R

Mar 31

Convolutional Neural Networks: Teaching Networks to See

#ai #convolutionalnetworks #computervision #machinelearning

4 min read

Nilavukkarasan R

Mar 13

Neural Network Regularization: Fighting Overfitting

#ai #machinelearning #regularization #weightdecay

4 min read

Nilavukkarasan R

Mar 4

Neural Network Optimizers: Training at Scale

#ai #neuralnetworks #deeplearning

3 min read

Nilavukkarasan R

Feb 19

Backpropagation: How Neural Networks Learn From Mistakes

#ai #backpropagation #machinelearning #neuralnetworks

4 min read

Nilavukkarasan R

Feb 17

Multi-Layer Perceptron: Where One Line Becomes Two

#ai #deeplearning #mlp

4 min read

Nilavukkarasan R

Feb 15

Perceptron: The Foundation of Modern AI

#perceptron #neuralnetworks #ai

3 min read

DEV Community

Nilavukkarasan R

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Writing Debut

The Transformer: The Architecture Behind Modern AI

Attention Mechanisms: Stop Compressing, Start Looking Back

Recurrent Neural Networks: Giving Networks Memory

Batch Normalization and Residual Connections: Going Deeper Without Breaking

Convolutional Neural Networks: Teaching Networks to See

Neural Network Regularization: Fighting Overfitting

Neural Network Optimizers: Training at Scale

Backpropagation: How Neural Networks Learn From Mistakes

Multi-Layer Perceptron: Where One Line Becomes Two

Perceptron: The Foundation of Modern AI