tomepel/Technical_Book_DL resource

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

1385 stars · 103 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A technical, pedagogical book (written in LaTeX, distributed as a PDF) explaining feedforward, convolutional, and recurrent neural network architectures with fully derived forward passes and backpropagation update rules. It is a learning resource, not software.

Use cases

• learn how backpropagation is derived step by step
• understand CNN and RNN building blocks with explicit index notation
• find a free deep learning textbook pdf
• study feedforward neural network math
• reference for LSTM and recurrent network equations
• supplement a deep learning course with detailed derivations

When to choose

• you prefer explicit index-level formulas over compact matrix notation
• you want full derivations of forward passes and backpropagation rules
• you need a free, citable technical reference on core neural architectures

When to avoid

• you want runnable code or implementations
• you need coverage of transformers or modern architectures
• you need a maintained, error-free resource - it has not been updated since 2019

Facets

learning-resource · maturity maintenance

deep-learning documentation deep-learning machine-learning tutorials artificial-intelligence cross-platform tex neural-networks backpropagation feedforward convolutional-networks recurrent-networks textbook pdf education

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