3 مستودعات
Tools for visually assessing and comparing the performance metrics of trained machine learning models through interactive plots and cross-validation results.
Distinct from Machine Learning Evaluation: Distinct from Machine Learning Evaluation: focuses on the visual, interactive evaluation interface rather than programmatic metric computation.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Visual Model Evaluators. Refine with filters or upvote what's useful.
This project is an educational resource providing practical code examples and implementations of machine learning algorithms using the Python language. It serves as a guide for constructing predictive pipelines, clustering models, and dimensionality reduction within the Scikit-Learn ecosystem. The repository includes comprehensive demonstrations for supervised and unsupervised learning, as well as detailed examples for implementing neural networks and deep architectures. It also provides practical guidance on exporting model parameters to JSON and wrapping trained models in web APIs for produ
Plots learning curves of accuracies against training set size to determine if more data improves performance.
Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
Ships a visual workbench with interactive model evaluation tools, performance curves, and cross-validation results.
Merlion هو إطار عمل لتعلم الآلة للسلاسل الزمنية مصمم للكشف عن الشذوذ والتنبؤ. يوفر واجهة موحدة لتنفيذ وتطبيق نماذج إحصائية ونماذج تعلم آلي متنوعة على تدفقات البيانات الزمنية. يتضمن المشروع لوحة تحكم للمقارنة المعيارية تسمح بالاختبار المرئي وتقييم النماذج مقابل مجموعات بيانات الحقيقة الأرضية التاريخية. تتيح واجهة الويب هذه تجربة نماذج مختلفة على مجموعات بيانات مخصصة دون الحاجة إلى برمجة يدوية. يغطي إطار العمل قدرات تحديد القيم المتطرفة، والتنبؤ بقيم السلاسل الزمنية المستقبلية، وقياس دقة النموذج من خلال الاختبار الخلفي القائم على المحاكاة لدورات تدريب الإنتاج.
Allows users to visually assess and compare the performance of various models on custom datasets via a dashboard.