Tag: Quantum ML & AI

Table of Contents Project Overview Motivation and Objectives Background and Literature Review Problem Statement Proposed Methodology Dataset Description and Preprocessing Quantum Circuit Design Classical-Quantum Hybrid Integration Model Training and Optimization Performance Evaluation Metrics Hardware and...

Table of Contents Introduction The Role of Recommendation Engines Classical Recommendation Techniques Why Quantum Machine Learning for Recommendation? Quantum Representations of Users and Items Quantum Feature Maps for Recommendation Variational Quantum...

Table of Contents Introduction Motivation for Structured QML Pipelines Comparison to Classical ML Workflows Key Components of a Quantum ML Pipeline Step 1: Data Collection and Preprocessing Step 2: Feature...

Table of Contents Introduction Why Model Compression Matters in QML Limitations of Large Quantum Models Types of Quantum Model Compression Circuit Pruning Techniques Gate Count Reduction and Depth Minimization Qubit Reduction...

Table of Contents Introduction Why Run QML on Real Quantum Hardware? Understanding NISQ Hardware Constraints Hardware Providers and Access Models QML-Friendly Devices: IBM, IonQ, Rigetti, OQC Circuit Depth, Qubit Count,...

Table of Contents Introduction Why PennyLane for QML? Installation and Setup PennyLane Architecture and Philosophy Devices and Backends Constructing Quantum Circuits Encoding Classical Data into Quantum States Variational Quantum Circuits (VQCs) Building a...

Table of Contents Introduction Why Use Qiskit for QML? Qiskit Machine Learning Overview Installing and Setting Up Qiskit ML Qiskit Data Encoding Techniques Feature Map Circuits for Classification Variational Quantum Classifiers...

Table of Contents Introduction Why Software Frameworks Matter in QML Overview of QML Framework Categories PennyLane: A Hybrid Quantum-Classical Framework Core Features of PennyLane Supported Interfaces and Backends Example Workflow in...

Table of Contents Introduction Importance of Security in ML Pipelines Quantum ML: New Threat Landscape Attack Surfaces in Quantum ML Systems Adversarial Attacks on Quantum Models Parameter Manipulation in Variational...

Table of Contents Introduction What Are Adversarial Attacks? Motivation for Studying Attacks in QML Classical Adversarial Attacks: A Brief Overview Unique Vulnerabilities in Quantum Models Types of Adversarial Attacks in...

Table of Contents Introduction What Is Federated Learning? Why Federated Learning Matters Quantum Federated Learning (QFL): Concept and Motivation Architecture of QFL Systems Quantum vs Classical Federated Learning QFL with Variational...

Table of Contents Introduction What Is Transfer Learning? Motivation for Transfer Learning in Quantum ML Classical vs Quantum Transfer Learning Types of Quantum Transfer Learning Pretraining Quantum Models Feature Extraction from...