priyam nagarUnveiling the Secrets of the Transformers — Part 1 EncoderWelcome to “Decoding Transformers,” where we embark on a journey into the intricate world of one of the most groundbreaking innovations in…Aug 21Aug 21
priyam nagarTransformers: Why Layer Normalization Wins Over Batch NormalizationNormalization is a method used to adjust input data so it fits within a specific range or pattern. This technique helps to even out…Aug 20Aug 20
priyam nagarMastering Positional Encoding: Enhancing Sequence Understanding in TransformersIn the realm of natural language processing (NLP), understanding the sequence and context of words is crucial. Traditional models like RNNs…Aug 8Aug 8
priyam nagarMastering English to Hindi Translation: Training a Transformer Model with Hugging FaceMachine translation has become an essential tool for bridging language barriers in our increasingly interconnected world. The challenge of…Jul 31Jul 31
priyam nagarUnlocking the Power of Multi-Head Attention: Revolutionizing Deep LearningIn deep learning, attention mechanisms help models focus on what’s important. Multi-head attention takes it a step further, allowing models…Jul 28Jul 28
priyam nagarUnpacking Self-Attention: The Backbone of Modern AIWhen Transformers revolutionized AI, they brought with them a game-changing concept: self-attention. This groundbreaking mechanism has…Jul 26Jul 26
priyam nagarFrom Problem to Solution: A Data Scientist’s Guide to Structured ThinkingAs a Data Scientist, we’re always faced with figuring out solutions to new problems that help us make smarter decisions. Surprisingly, many…Feb 25Feb 25
