data-science
-
Understanding Backpropagation: A Comprehensive Guide to Neural Network Learning
Introduction Backpropagation is a fundamental algorithm in the training of neural networks, enabling these complex systems to learn from data and improve their performance over time. This guide aims to demystify the backpropagation process, explaining its core concepts and significance in machine learning. The Objective of Neural Networks The primary goal of a neural network Continue reading
-
FLOAT32, FLOAT16, AND BFLOAT16: PRECISION’S ROLE IN DEEP LEARNING
(continued from previous section) 🟧 Impact on Deep Learning Processes The choice of floating-point format significantly affects various aspects of deep learning, including training speed, memory usage, and computational accuracy. Let’s explore these impacts in detail. Training Speed The precision format directly influences the speed of neural network training: Many deep learning frameworks now support Continue reading
Think like a butterfly 