Jupyter Notebook pennylane

Open-source Jupyter Notebook projects categorized as pennylane
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Qml quantum-computing Qiskit Quantum Jax
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Top 5 Jupyter Notebook pennylane Projects

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  1. QMLDocker

    A docker container for quantum machine learning (QML) research

  2. Kargo

    Stop Scripting Promotions. Start Shipping with Kargo. Kargo automates promotion across dev, staging, and prod with approval gates and verification. Open source, built by the team behind Argo CD. Download now.

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  3. quoptuna

    Fairness-aware, explainable AutoML for quantum + classical ML — 21 models, one Optuna search, SHAP & AI reports. uvx quoptuna

    Project mention: I built AutoML for quantum machine learning — here's the architecture | dev.to | 2026-07-19

    TL;DR — uvx quoptuna boots a full AutoML web app with no install. It runs one hyperparameter search across 21 quantum and classical classifiers, prunes weak configs early, audits every model for fairness, explains the winner with SHAP, and can draft the report for you. Apache-2.0. Repo: github.com/Qentora/quoptuna. Stars and feedback very welcome. ⭐

  4. spinq-vqe

    VQE simulation of the Kagome antiferromagnet (Mn₃Sn) — HEA & MERA ansatze, entanglement entropy, ED benchmarks, SOC QAOA.

    Project mention: Simulating Antiferromagnets with PennyLane: A Deep Dive into spinq-vqe | dev.to | 2026-06-25

    Quantum Machine Learning (QML) is rapidly moving from theoretical whitepapers into practical engineering pipelines. If you are curious about how quantum algorithms actually interface with material science, the newly open-sourced spinq-vqe repository from ARPA's QONDRA division is a perfect sandbox.

  5. EuroPython-21-QuantumDeepLearning

    Materials and Resources for the EuroPython 21 Talk on "Introduction to Quantum Deep Learning" on 28/7/2021.

  6. trainable-qsp-angles

    Reproducible QSP benchmark: gradient-learned phase angles on a JAX flat circuit vs mapped analytic solvers.

    Project mention: You Can Now Train Quantum Signal Processing Phase Angles with Gradient Descent | dev.to | 2026-06-11

    A new paper and open‑source implementation (DOI: 10.5281/zenodo.20645403, github.com/rosspeili/trainable-qsp-angles) shows that you can learn QSP phase angles from random initialization using gradient descent – with no analytic pre‑computation.

  7. AppSignal

    Monitoring that respects your time & budget. APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.

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NOTE: The open source projects on this list are ordered by number of github stars. The number of mentions indicates repo mentiontions in the last 12 Months or since we started tracking (Dec 2020).

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Jupyter Notebook pennylane related posts

  • My EuroPython '21 talk on Quantum Deep Learning

    1 project | dev.to | 19 Aug 2021

Index

What are some of the best open-source pennylane projects in Jupyter Notebook? This list will help you:

# Project Stars
1 QMLDocker 46
2 quoptuna 19
3 spinq-vqe 5
4 EuroPython-21-QuantumDeepLearning 3
5 trainable-qsp-angles 2

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