EigenAlpha
EigenAlpha is made and published by JT Scientific Consulting LLC. AppBrain is an independent app data site and isn't affiliated with JT Scientific Consulting LLC. The app name, icon, screenshots and description belong to JT Scientific Consulting LLC and are shown as published on the App Store.
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- Last updated
- May 26, 2026
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Releases
Updates seen on the App Store- Version
- 1.0
- Launched
- May 2026
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Technology
Found in the app by AppBrain- Price
- Free
- App size
- 6.85 MB
- Content rating
- Everyone
Technologies used by EigenAlpha
About the app and developer
About EigenAlpha
EigenAlpha is an education app developed by JT Scientific Consulting LLC.
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App Information
EigenAlpha is freely available from the App Store. The app size is 6.85 MB. The latest version available is 1.0. The last update was on May 26, 2026.
Technical Requirements
The app has a content rating of Everyone. The app has been available on the App Store since May 2026.
Developer information for JT Scientific Consulting LLC
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By JT Scientific Consulting LLC, from the App Store
Description by JT Scientific Consulting LLC Written by the developer, not by AppBrain. Click to read.
Unlock the visual and spatial power of Linear Algebra. EigenAlpha is an interactive learning console designed for university students, engineers, and machine learning enthusiasts who want to develop a deep, intuitive, and mathematical grasp of vector spaces, matrices, and linear mappings.
Skip rote memorization. EigenAlpha combines structured curriculum progression with stunning visual diagnostics to help you bridge the gap between abstract equations and geometric transformations.
KEY FEATURES:
Structured Course Progression: Move step-by-step through core Linear Algebra units—from basis vector spans and matrix dimensions to QR decompositions, eigenvalues, and Gram-Schmidt orthogonalization.
Macro Skill Diagnostics: View your real-time accuracy across 6 core mathematical domains, including Matrix Arithmetic, Algorithmic Reduction (Gaussian Elimination), Spectral Decomposition, and Invariant Inspection.
Applied Crossover Case Studies: Explore how abstract matrix concepts drive state-of-the-art modern technologies. Follow step-by-step reasoning progressions for real-world scenarios, including Google PageRank spectral convergence.
Conceptual Diagrams & Pitfalls: Review custom high-contrast visuals mapping out transformations and eigenvalues. Learn to bypass common pitfalls and exam tips carefully curated by math researchers.
Reset & Restore Control: Maintain full command over your learning log. Reset diagnostic progress to re-test your accuracy, and easily restore premium license entitlements across all your iOS devices.
Accessibility Integrated: Fully optimized for Dynamic Type font scaling and screen reader VoiceOver narration.
WHO IS IT FOR?
- STEM Undergrads: Excel in college-level Linear Algebra courses and diagnostic exams.
- AI & Machine Learning Developers: Understand the vector transformations, dimension spaces, and spectral decomposition behind neural networks and PCA.
- 3D Developers & Graphics Engineers: Master translation, rotation, and projection matrices.