6 articles with this tag.
A deep dive into Recurrent Neural Networks and Long Short-Term Memory networks. Learn how they process sequences, why vanilla RNNs fail, and how LSTMs solve the vanishing gradient problem.
A complete beginner's guide to ReLU (Rectified Linear Unit) - what it is, why it works so well, and how to use it in neural networks with clear examples.
Learn how backpropagation works through a simple, step-by-step example. Understand the chain rule intuitively with clear visualizations and working code.
A complete beginner's guide to Batch Normalization - what it is, why it works, how to implement it, and the critical train vs eval mode difference that trips up everyone.
A complete beginner's guide to Dropout regularization - why randomly turning off neurons makes neural networks smarter, how it works, and how to use it correctly in PyTorch.
A beginner-friendly guide to pretrained sentence embeddings, multi-layer perceptrons, and the building blocks that make modern NLP work β explained with simple examples and zero jargon.