Coding Positional Encoding from Scratch (Python & NumPy Tutorial) | Part 3 скачать в хорошем качестве

Coding Positional Encoding from Scratch (Python & NumPy Tutorial) | Part 3

In the finale of our Positional Encoding series, we stop talking theory and start coding. We take the mathematical formulas derived in Part 2 and implement them in Python from scratch. We start with a "naive" loop-based approach to understand the logic line-by-line. Then, we refactor the code into a professional, vectorized implementation using NumPy broadcasting—the standard way this is done in modern Deep Learning frameworks like PyTorch or TensorFlow. Finally, we generate the famous "Heatmap" visualization to prove our code works. In this video, we cover: • The Naive Implementation: Translating the sin/cos formulas directly into Python loops. • Vectorization: How to speed up the code by 100x using NumPy broadcasting. • Verification: Comparing our code's output against manual calculations. • Visualization: Generating the classic Blue/Red frequency heatmap using Matplotlib. • Integration: How to properly add these encodings to your word embeddings (and why we sum them instead of concatenating). #Transformers #Python #DeepLearning #NumPy #NLP #CodingTutorial #PositionalEncoding