Vector Retrieval Techniques and Algorithms

Introduction to Vector DBMS, vector retrieval techniques and design patterns, sample code, examples

Selected Topics in Machine Learning

• Reinforcement Learning and Game Theory

• Offline Reinforcement and Self-Supervised Learning

• NLP Concepts

• Transformers

• Large Language Models

• Bayesian Networks

• Probabilistic Machine Learning and Bayesian Methods

• Statistical Learning, Kernel Methods, Kolmogorov-Arnold Networks

• Optimization, Classification, Regression

• Causal Inference, Root Cause Analysis and Model Checking

• Image Processing and Computer Vision: Techniques and Algorithms

• Deep Learning and Neural Networks

• Deep Learning for solving Image Processing problems and Generative Tasks

• Deep Learning Models for Time Series Forecasting problems

• Deep Learning Models for Dynamical System Analysis

• Vector Retrieval Techniques and Algorithms

• Retrieval-Augmented Generation Concepts, Architectures and Algorithms

• Hypothesis Testing, Estimation of Treatment Effects and Generalized Synthetic Control

• Graphs and Dynamic Programming

• Dynamical Systems, State-Space Models, Chaos, Ergodicity

• Information Theory, Statistical Mechanics, Diffusion Models

• Queueing Networks, Queueing Theory, Reversible Stochastic Processes

• Spectral Analysis, Optimization in Spectral Domain, Spectral Domain Modeling

• Computability, Automata, Logic Systems, Formal Grammars and Theory of Parsing

• Thought Forming, Consciousness, Intelligent Machines, Semantic Inference

Note

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