deeplearningfoundationsandconcepts

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
deeplearningfoundationsandconcepts [2025/05/05 11:26] gedbadmindeeplearningfoundationsandconcepts [2025/05/05 11:30] (current) gedbadmin
Line 1: Line 1:
 ====== Table of Contents ====== ====== Table of Contents ======
  
-  - [[>OneDeepLearningRevolution|The Deep Learning Revolution]]+  - [[~:OneDeepLearningRevolution|The Deep Learning Revolution]]
     - The Impact of Deep Learning     - The Impact of Deep Learning
     - A Tutorial Example     - A Tutorial Example
     - A Brief History of Machine Learning     - A Brief History of Machine Learning
-  - [[>TwoProbabilities|Probabilities]]+  - [[~:TwoProbabilities|Probabilities]]
     - The Rules of Probability     - The Rules of Probability
     - Probability Densities     - Probability Densities
Line 12: Line 12:
     - Information Theory     - Information Theory
     - Bayesian Probabilities     - Bayesian Probabilities
-  - [[>ThreStandardDistributions|Standard Distributions]]+  - [[~:ThreStandardDistributions|Standard Distributions]]
     - Discrete Variables     - Discrete Variables
     - The Multivariate Gaussian     - The Multivariate Gaussian
Line 21: Line 21:
     - Kernel densities     - Kernel densities
     - Nearest-neighbours     - Nearest-neighbours
-  - [[>FourSingleLayerNetworksRegression|Single Layer Networks: Regression]]+  - [[~:FourSingleLayerNetworksRegression|Single Layer Networks: Regression]]
     - Linear Regression     - Linear Regression
     - Decision Theory     - Decision Theory
     - The Bias-Variance Trade-off     - The Bias-Variance Trade-off
-  - [[>FiveSingleLayerNetworksClassification|Single-layer Networks: Classification]]+  - [[~:FiveSingleLayerNetworksClassification|Single-layer Networks: Classification]]
     - Discrimination Functions     - Discrimination Functions
     - Decision Theory     - Decision Theory
     - Generative Classifiers     - Generative Classifiers
     - Discriminative Classifiers     - Discriminative Classifiers
-  - [[>SixDeepNeuralNetworks|Deep  Neural Networks]]+  - [[~:SixDeepNeuralNetworks|Deep  Neural Networks]]
     - Limitations of Fixed Basis Functions     - Limitations of Fixed Basis Functions
     - Mulilayer Networks     - Mulilayer Networks
Line 36: Line 36:
     - Error Functions     - Error Functions
     - Mixture Density Networks     - Mixture Density Networks
-  - [[>SevenGradientDescent|Gradient Descent]]+  - [[~:SevenGradientDescent|Gradient Descent]]
     - Error Surfaces     - Error Surfaces
     - Gradient Descent Optimization     - Gradient Descent Optimization
Line 43: Line 43:
     - Batch Normalization     - Batch Normalization
     - Layer Normalization     - Layer Normalization
-  - [[>EightBackpropegation|Backpropegations]]+  - [[~:EightBackpropegation|Backpropegations]]
     - Evaluation of Gradients     - Evaluation of Gradients
     - Automatic Differntiation     - Automatic Differntiation
-  - [[>NineRegularization]]+  - [[~:NineRegularization]]
     - Induction Bias     - Induction Bias
     - Weight Decay     - Weight Decay
Line 53: Line 53:
     - Residual Connections     - Residual Connections
     - Model Averaging     - Model Averaging
-  - [[>TenConvolutionalNetworks|Convolutional  Networks]]+  - [[~:TenConvolutionalNetworks|Convolutional  Networks]]
     - Computer Vision     - Computer Vision
     - Convulutional Filters     - Convulutional Filters
     - General Graph Networks     - General Graph Networks
-  - [[>EleventStructuredDistributions|Structured Distributions]]+  - [[>~:EleventStructuredDistributions|Structured Distributions]]
     - Graphical Models     - Graphical Models
     - Conditional Independence     - Conditional Independence
     - Sequence Models     - Sequence Models
-  - [[>TwelveTransforms|Transformers]]+  - [[~:TwelveTransforms|Transformers]]
     - Attention     - Attention
     - Natural Language     - Natural Language
     - Transformer Language Models     - Transformer Language Models
     - Multimodal Transformers]]     - Multimodal Transformers]]
-  - [[>ThirteenGraphNeuralNetworks|Graph Neural Networks]]+  - [[~:ThirteenGraphNeuralNetworks|Graph Neural Networks]]
     - Machine Learning on Graphs     - Machine Learning on Graphs
     - Neural Message-Passing     - Neural Message-Passing
     - General Graph Networks     - General Graph Networks
-  - [[>FourteenSampling|Sampling]]+  - [[~:FourteenSampling|Sampling]]
     - Basic Sampling Algorithms     - Basic Sampling Algorithms
     - Markov Chgain Monte Carlo     - Markov Chgain Monte Carlo
     - Langevin Sampling     - Langevin Sampling
-  - [[>FifteenLatentVariables]]+  - [[~:FifteenLatentVariables]]
     - k-means Clustering     - k-means Clustering
     - Mixture of Gaussians     - Mixture of Gaussians
     - Expectation-Maximizastion Algorithm     - Expectation-Maximizastion Algorithm
     - Evidence Lower Bound     - Evidence Lower Bound
-  - [[>SixteenContinuousLatentVariables|Continuous Latent Variables]]+  - [[~:SixteenContinuousLatentVariables|Continuous Latent Variables]]
     - Principal Component Analysis     - Principal Component Analysis
     - Probabilistic Latent Variables     - Probabilistic Latent Variables
     - Evidence Lower Bound     - Evidence Lower Bound
     - Nonlinear Latent Variable Models     - Nonlinear Latent Variable Models
-  - [[>SeventeenGenerativeAdversarialNetworks|Generative Adversarial Networks]]+  - [[~:SeventeenGenerativeAdversarialNetworks|Generative Adversarial Networks]]
     - Adversarial Training     - Adversarial Training
     - Image GANs     - Image GANs
-  - [[>EighteenNormalizingFlows|Normalizing Flows]]+  - [[~:EighteenNormalizingFlows|Normalizing Flows]]
     - Coupling Flows     - Coupling Flows
     - Autoregressive Flows     - Autoregressive Flows
     - Continuous Flows     - Continuous Flows
-  - [[>NineteenAutoencoders|Autoencoders]]+  - [[~:NineteenAutoencoders|Autoencoders]]
     - Deterministic Autoencoders     - Deterministic Autoencoders
     - Variational Autoencoders     - Variational Autoencoders
-  - [[>TwentyDiffusionModels|Diffusion Models]]+  - [[~:TwentyDiffusionModels|Diffusion Models]]
     - Forward Encoder     - Forward Encoder
     - Reverse Encoder     - Reverse Encoder
Line 101: Line 101:
  
   * Appendices   * Appendices
-    - [[>A1LinearAlgebra|Linear Algebra]] +    - [[~:A1LinearAlgebra|Linear Algebra]] 
-    - [[>A2CalculusOfVariations|Calculus of Variations]] +    - [[~:A2CalculusOfVariations|Calculus of Variations]] 
-    - [[>A3LagrangeMultipliers|Lagrange Multipliers]]+    - [[~:A3LagrangeMultipliers|Lagrange Multipliers]]
  
  
  • deeplearningfoundationsandconcepts.txt
  • Last modified: 2025/05/05 11:30
  • by gedbadmin