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Quantum Nearest-Neighbor Models: Leveraging Quantum Metrics for Pattern Recognition

Kumar Prafull -
Table of Contents Introduction Classical k-Nearest Neighbors (k-NN) Overview Motivation for Quantum k-NN (QkNN) Quantum State Similarity Measures Encoding Classical Data into Quantum States Distance Metrics in Quantum Space Quantum Fidelity...

Variational Quantum Classifiers: A Hybrid Approach to Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction What Are Variational Quantum Classifiers (VQCs)? Why Use Variational Circuits for Classification? Key Components of a VQC Quantum Data Encoding Ansatz Design for Classification Measurement and Output...

Feature Maps and Quantum Kernels: Enhancing Machine Learning with Quantum Embeddings

Kumar Prafull -
Table of Contents Introduction Classical Feature Maps and Kernels Why Quantum Feature Maps? Basics of Quantum Kernel Methods Embedding Data into Hilbert Space Types of Quantum Feature Maps ZZFeatureMap PauliFeatureMap Custom Feature Maps...

Encoding Classical Data into Quantum States: Foundations and Techniques

Kumar Prafull -
Table of Contents Introduction Why Encoding Matters in Quantum Machine Learning Characteristics of Quantum Data Representations The Challenge of Data Input in QML Types of Quantum Data Encoding Basis Encoding Amplitude...

Classical vs Quantum ML Approaches: A Comparative Overview

Kumar Prafull -
Table of Contents Introduction Defining Classical Machine Learning Defining Quantum Machine Learning Theoretical Foundations of Classical ML Theoretical Foundations of Quantum ML Data Representation in Classical vs Quantum ML Model Architectures...

Introduction to Quantum Machine Learning: Merging Quantum Computing with AI

Kumar Prafull -
Table of Contents Introduction What Is Quantum Machine Learning (QML)? Why Combine Quantum and Machine Learning? Key Concepts Behind QML Qubits, Superposition, and Entanglement Classical vs Quantum ML Pipelines Data Encoding...
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