Скачать или смотреть Beyond the Buzzwords: How Neural Networks Actually Learn

Join us for a deep dive into the fundamental algorithms of neural networks: Backpropagation, Gradient Descent, and Stochastic Gradient Descent. We will walk through the logic behind these concepts and solidify your understanding by building a working Perceptron from scratch in Google Colab. Perfect for developers who want to understand the "why" behind the code.

Key learning objectives
1. Deconstruct the Math: Gain a clear, intuitive understanding of Backpropagation and how it calculates gradients to minimize error and drive learning.
​2. Master Optimization Strategies: Learn the mechanics of Gradient Descent and differentiate it from Stochastic Gradient Descent (SGD) to understand how models efficiently find optimal solutions.
​3. Build from First Principles: Apply theory to practice by implementing a Perceptron from scratch in Python to see exactly how weights and biases are updated code-line by code-line.