Subscribe

Quantum 101

HomeQuantum 101

Implementing Quantum Machine Learning on Real Hardware: From Simulation to Execution

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,...
Kumar Prafull - 0

Hands-On Quantum Machine Learning with PennyLane

0

Experimenting with Quantum Machine Learning in Qiskit

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...
Kumar Prafull - 0

Software Frameworks for Quantum Machine Learning: Exploring PennyLane, TensorFlow Quantum, and More

0

― Advertisement ―

spot_img

Cross-Validation for Quantum Models: Enhancing Reliability in Quantum Machine Learning

Table of Contents Introduction Why Cross-Validation Matters in QML Classical Cross-Validation Refresher Challenges in Quantum Cross-Validation Quantum-Specific Noise and Variance k-Fold Cross-Validation in Quantum Context Leave-One-Out and Holdout Validation Data Splitting and...

More News

Explainability and Interpretability in Quantum Machine Learning

Table of Contents Introduction Why Interpretability Matters in Machine Learning Unique Challenges in Explaining Quantum Models Definitions: Explainability vs Interpretability Black-Box Nature of Quantum Circuits Quantum Measurement and Information Loss Interpretable...

Analyzing Complexity in Quantum Machine Learning: Theoretical Foundations and Practical Implications

Table of Contents Introduction Importance of Complexity Analysis in QML Classical Complexity Basics Quantum Complexity Classes Relevant to QML BQP, QMA, and QML Algorithms Time and Space Complexity in QML Circuit...

Quantum Machine Learning in Image Recognition: A New Frontier in Visual Intelligence

Table of Contents Introduction Why Image Recognition Matters Classical Challenges in Visual AI Quantum Advantages for Image Processing Encoding Images into Quantum Circuits Angle, Basis, and Amplitude Encoding Quantum Feature Extraction Variational...

Explore more

Quantum Overfitting and Regularization: Enhancing Generalization in Quantum Models

Kumar Prafull -
Table of Contents Introduction What Is Overfitting in Machine Learning? Manifestation of Overfitting in Quantum Models Sources of Overfitting in Quantum Machine Learning Variational Quantum Circuits and Model Complexity Role...

Gradient Descent in Quantum Landscapes: Navigating Optimization in Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction Understanding Quantum Loss Landscapes What Is Gradient Descent? Role of Gradients in Quantum Circuit Training Challenges Unique to Quantum Landscapes Variational Quantum Circuits and Cost Minimization The...

Auto-Differentiation in Quantum Circuits: Enabling Gradient-Based Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction What Is Auto-Differentiation? Why Gradients Matter in Quantum ML Variational Quantum Circuits and Parameter Training Challenges of Differentiation in Quantum Systems Classical vs Quantum Auto-Differentiation Forward and...

Optimization Techniques in Quantum Machine Learning: SPSA, COBYLA, and Beyond

Kumar Prafull -
Table of Contents Introduction Role of Optimization in Quantum Machine Learning Gradient-Based vs Gradient-Free Methods Stochastic Gradient Descent (SGD) Adam Optimizer Simultaneous Perturbation Stochastic Approximation (SPSA) SPSA: Algorithm and Use Cases SPSA...

Backpropagation with Parameter-Shift Rule in Quantum Models

Kumar Prafull -
Table of Contents Introduction Need for Gradients in Quantum ML Variational Quantum Circuits and Training Limitations of Classical Backpropagation The Parameter-Shift Rule: Core Concept Mathematical Derivation Conditions for Using Parameter-Shift Rule General...

Training Quantum Models: Optimizing Parameters for Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction What Does Training Mean in Quantum ML? Variational Quantum Circuits (VQCs) as Models Cost Functions and Objective Definitions Forward Pass: Circuit Evaluation Measurement and Output Processing Gradient...

Cost Functions for Quantum Models: Measuring Performance in Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction Role of Cost Functions in QML Characteristics of a Good Cost Function Cost Functions for Classification Binary Cross-Entropy Loss Mean Squared Error (MSE) Hinge Loss for Margin-Based...

Variational Circuits in ML Workflows: Quantum Layers for Learnable Representations

Kumar Prafull -
Table of Contents Introduction What Are Variational Quantum Circuits (VQCs)? Why Use VQCs in Machine Learning? Structure of a Variational Circuit Parameterized Quantum Gates Designing Expressive Circuit Architectures Encoding Classical Data...

Quantum Reinforcement Learning: Merging Quantum Computing with Adaptive Decision Making

Kumar Prafull -
Table of Contents Introduction Classical Reinforcement Learning Overview What is Quantum Reinforcement Learning (QRL)? Why Quantum for Reinforcement Learning? QRL Frameworks and Paradigms Quantum Agents and Environments Quantum Policy Representation Quantum Value...

Hybrid Neural Networks: Merging Classical and Quantum Models for Intelligent Learning

Kumar Prafull -
Table of Contents Introduction What Are Hybrid Neural Networks? Why Combine Classical and Quantum Layers? General Architecture of Hybrid Models Quantum Layers in Classical Pipelines Classical Preprocessing and Postprocessing Variational Quantum...

Data Re-uploading Strategies in Quantum Machine Learning

Kumar Prafull -
Table of Contents Introduction The Challenge of Expressivity in Quantum Circuits What Is Data Re-uploading? Motivation Behind Data Re-uploading Mathematical Foundation of Re-uploading Circuit Architecture with Re-uploading Implementation Techniques Periodic vs Adaptive...

Quantum GANs – Generative Adversarial Networks: Quantum Approaches to Data Generation

Kumar Prafull -
Table of Contents Introduction Classical GANs: A Brief Overview Motivation for Quantum GANs Structure of a Quantum GAN (QGAN) Quantum Generator: Circuit-Based Design Quantum Discriminator Options Hybrid Classical-Quantum Architectures Objective Functions and...
123...32Page 1 of 32

Subscribe for exclusive content

We have a curated list of the most noteworthy news from all across the globe. With any subscription plan, you get access to exclusive articles that let you stay ahead of the curve.

Subscribe

Copyright Syskool.