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Deep Learning / 03

Neural Network Fundamentals

Explore neurons, weights, biases, activations, layers, and computational graphs.

Section 3 of 32 · 17 subtopics

This is a knowledge index. Published titles open their articles; the remaining entries outline planned coverage.

Deep Learning / deep dive

Simple operations. Learned representations.

Follow a signal through a neural network, then follow the error back to understand what training changes.

Subtopics

  1. 03.01

    Artificial Neuron

    Planned guide: Artificial Neuron. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  2. 03.02

    Inputs

    Planned guide: Inputs. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  3. 03.03

    Weights

    Planned guide: Weights. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  4. 03.04

    Bias

    Planned guide: Bias. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  5. 03.05

    Weighted Sum

    Planned guide: Weighted Sum. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  6. 03.06

    Activation Function

    Planned guide: Activation Function. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  7. 03.07

    Layers

    Planned guide: Layers. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  8. 03.08

    Input Layer

    Planned guide: Input Layer. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  9. 03.09

    Hidden Layers

    Planned guide: Hidden Layers. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  10. 03.10

    Output Layer

    Planned guide: Output Layer. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  11. 03.11

    Dense / Fully Connected Layer

    Planned guide: Dense / Fully Connected Layer. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  12. 03.12

    Network Depth

    Planned guide: Network Depth. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  13. 03.13

    Network Width

    Planned guide: Network Width. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  14. 03.14

    Parameters

    Planned guide: Parameters. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  15. 03.15

    Computational Graphs

    Planned guide: Computational Graphs. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  16. 03.16

    Multi-Layer Perceptron

    Planned guide: Multi-Layer Perceptron. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation
  17. 03.17

    Universal Approximation Intuition

    Planned guide: Universal Approximation Intuition. Focus on intuition, assumptions, and a worked example.

    beginnerArticle in preparation