Index - Deep Learning

Info about the Document

Author: Domiziano Scarcelli Course: Blockchain and Distributed Ledger Technologies (2022-2023) Sources: Prof. Emanuele Rodolà and guest’s Slides and Lectures, along with the Python Notebooks provided during the course.

Disclaimer: the notes may not be complete or correct, so take them as a reference and not as the only material for your study.

Table of Contents

• Definition of Deep Learning
• Data in Machine Learning
• Linear Algebra Revisited
  • Vector Space
  • Linear Maps
  • Matrix
  • Vector Lengths and Distances
• Linear Models
  • Linear Regression
  • Jensen’s inequality
• Non-Linear Models
  • Polynomial Regression
• Classification
  • Logistic Regression
• Gradient Descent
  • Gradient
  • Backpropagation
• Multi Layer Perceptron
  • Deep ReLU Networks
• Convolutional Neural Networks
  • Invariances and Equivariances
  • CNN vs MLP
• Regularization
  • Dropout
  • Batch Normalization
  • Early Stopping
• Double Descent
• Generative Models
  • PCA - Principal Component Analysis
  • Autoencoders
  • Manifold Hypothesis
  • Entropy
• Geometric Deep Learning
• Sequence Models
  • Transformers
• Generative Adversarial Networks
  • Adversarial Attacks on GANs