DijkstraGraph vs EigenAlpha

Learn, Play, and Explore graph theory and Dijkstra's shortest path algorithm with DijkstraGraph! Create and edit simple graphs and add edge weights. Rearrange the vertices and interact with the adjacency matrix to explore graph and matrix structure. Play through Dijkstra's shortest path algorithm step by step to identify a shortest path between two vertices. Play through the algorithm on the connected graph you create or explore one already created for you! Create and edit simple graphs - Add and delete vertices and edges - Add and edit weights on each edge - Rearrange vertices to explore graph Interact with the adjacency matrix - Tap on a vertex or edge to highlight corresponding rows and columns in adjacency matrix Play or Explore Dijkstra's shortest path algorithm - Play through Dijkstra's shortest path algorithm on the graph you create! - Or Explore the algorithm on a built in demo graph - Choose a start and end vertex then follow the instructions to step through the algorithm - Complete each step successfully to advance to the next part of the algorithm - After completing the algorithm, use the results to identify the shortest path Run - Don't have time to play through the algorithm?  - Choose a start and end vertex and run the algorithm to identify shortest path

EigenAlpha: Linear Algebra Core Skills Training 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.