Microsoft Power BI Guide — Part 3(Preparing the Environment and Getting Started)
Microsoft Power BI Guide — Part 3(Preparing the Environment and Getting Started)
Before diving into our Power BI project, it’s essential to set up the environment correctly to ensure consistency and avoid potential…
Microsoft Power BI Guide — Part 2(Getting Familiar with Power BI through a Mini Project)
Microsoft Power BI Guide — Part 2(Getting Familiar with Power BI through a Mini Project)
Before diving into complex projects, it’s crucial to become familiar with the Power BI interface and understand its core functionalities…
The decoder stack in the Transformer model
The decoder stack in the Transformer model
The decoder stack in the Transformer model, much like its encoder counterpart, consists of several layers, each featuring three main…
Lung Localization with Pytorch Lighnining
Lung Localization with Pytorch Lighnining
Over the last decade, deep learning, particularly Convolutional Neural Networks (CNNs), has significantly advanced the field of medical…
The Feedforward Network (FFN) in The Transformer Model
The Feedforward Network (FFN) in The Transformer Model
The Transformer model revolutionizes language processing with its unique architecture, which includes a crucial component known as the…
Post-Layer Normalization
Post-Layer Normalization
In the intricate architecture of the Transformer, Post-Layer Normalization (Post-LN) plays a pivotal role in stabilizing the learning…
Exploring the Multi-head Attention Sublayer in the Transformer
Exploring the Multi-head Attention Sublayer in the Transformer
The multi-head attention mechanism is a hallmark of the Transformer model’s innovative approach to handling sequential data. It enhances…