Dimitar Gueorguiev's repositories
reinforcement_learning_and_game_theory
Collection of materials and code samples on reinforcement learning / optimal control and game theory
root_cause_analysis_and_model_checking
Causal Inference, RCA algorithms, Probabilistic graph models based on Markov Chains, Model verification through Probabilistic Temporal Logic
aiconcepts
work in progress on the Theory of Semantic Structures
transformers_intro
Intro to Transformers
cnn_image_classification
CNN examples for image classification
computability_and_logic_systems
Computability, Logic Systems, Formal Grammars and Theory of Parsing
deep_learning_and_neural_networks
Connectionist architectures, Deep Learning and Neural Nets articles, papers, tutorials and books
deep_learning_for_dynamical_systems
Neural networks and Deep Learning algorithms applied to dynamical systems and their evolution through time
deep_learning_for_image_processing
Deep Learning architectures and algorithms for solving image processing problems
deep_learning_for_time_series_forecasting
Various Deep Learning models suitable for time series forecasting
dynamical_systems_and_ergodicity
Study of dynamical systems, chaos theory and ergodic systems
generalized_synthetic_control_for_testops
A new method for conducting testing on large scale extracting statistically significant data from noisy experiments
graphs_and_dynamic_programming
Texts and source on the topic of Theory of Graphs, Grpah Networks, Max Flow Problems and dynamic programming
image_processing
Image Processing Algorithms in Python
information_theory_and_statistical_mechanics
Study materials on Information Theory and its relations with physical systems models
JavaScript_for_web_dev
Java Script for Web Development: sample code books and articles
learning_bayesian_networks
supplementary material to Learning Bayesian Networks by R Neapolitan
nlp_concepts
NLP tutorials, articles, books and source code illustrating concepts
optimization_classification_regression
repo for fundamental Machine Learning methods: classic linear and non-linear optimization, classification algorithms and regression techniques and methods
PDF-Extract-Kit
A Comprehensive Toolkit for High-Quality PDF Content Extraction
probabilistic_machine_learning
Discussion around Murphy's book "ML - A Probabilistic Perspective"
quantum_computing_and_algorithms
Quantum Computing Advances and Related Algorithms
queueing_theory
Queueing Theory and Stochastic Networks
self_supervised_learning
Materials on Offline Reinforcement and Self Supervised Learning
semantic_segmentation_demo
Semantic Segmentation with ResNet-18
spectral_analysis
Frequency domain analisys, stochastic techniques and data processing algorithms
statistical_learning_and_kernel_methods
Statistical Learning Theory and Algorithms, Kernel Methods, KAN networks, Support Vector Machines
typescript_testcode
typescript test code