Articles

Neural Network

Weight Initialization Matters More Than You Think

Poor weight initialization causes vanishing or exploding gradients before training even begins. Lear...

Mar 22, 2026 Read more

Neural Network

Residual Connections Explained: The Trick That Made Deep Networks Trainable

Residual connections solved the degradation problem in deep networks, enabling training of networks...

Mar 22, 2026 Read more

Neural Network

Batch Normalization vs Layer Normalization: When to Use Which

Batch normalisation and layer normalisation are both widely used but serve different use cases. Unde...

Mar 22, 2026 Read more

Neural Network

Pruning Neural Networks for Deployment Without Killing Performance

Neural network pruning removes redundant weights to reduce model size and inference latency. Learn u...

Mar 22, 2026 Read more

Neural Network

Understanding Vanishing Gradients Through the Lens of Network Depth

Vanishing gradients are the fundamental reason deep neural networks were untrainable before 2015. Un...

Mar 22, 2026 Read more

Neural Network

Recurrent vs Convolutional Architectures for Sequential Data: A Fair Comparison

RNNs and CNNs both process sequential data but with fundamentally different inductive biases. In pra...

Mar 22, 2026 Read more

Neural Network

Hyperparameter Tuning Beyond Grid Search: Smarter Strategies for Deep Networks

Grid search is the worst way to tune hyperparameters. Learn how random search, Bayesian optimisation...

Mar 22, 2026 Read more

Neural Network

Interpreting Neural Network Decisions With Activation Maps

Activation maps and gradient-based attribution methods make neural network decisions interpretable b...

Mar 22, 2026 Read more

Neural Network

Continual Learning: Teaching Neural Networks New Tricks Without Forgetting Old Ones

Continual learning addresses catastrophic forgetting — the tendency of neural networks to lose previ...

Mar 22, 2026 Read more

Neural Network

Knowledge Distillation: Compressing a Large Network Into a Deployable Model

Knowledge distillation transfers the learned representations of a large teacher network into a small...

Mar 22, 2026 Read more