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WS23_AKIDS1
Lectures
L10: Graphs
L10: Graphs
Requisitos de conclusão
Clique na hiperligação
L10_Graphs.pdf
para ver o ficheiro.
◄ L9: Balanced Trees (AVL)
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L1: Introduction
L2: Algorithms
L3: Data Structures
L4: Algorithmic Complexity
L5: Sorting
L6: Heap
L7: Hashing
L8: Binary Search Tree
L9: Balanced Trees (AVL)
L11: Graph Algorithms
L12: Dynamic Programming
L13: DP Problems
L14: State Space Search
L15: Heuristic State Space Search
L16: Adversarial Search (Game Playing)
L17: Metaheuristic Search (Discrete Optimization)
L18: Constraint Satisfaction and Backtracking
L19: Knowledge-Based Reasoning (Expert Systems)
L20: Numeric(al) Optimization
L21: Introduction to Machine Learning
L22: Parametric Classification
L23: Non-Parametric Classification
Probeklausur
Hauptklausur (13.2.): Results and Grades
Nachholklausur (11.4.): Results and Grades
Exercise 0 - Introduction to Python
Exercise 01 - Stack & Queue
Exercise 01 - Stack & Queue - Solutions
Exercise 02 - Complexity & Sorting
Exercise 02 - Complexity & Sorting - Solutions
Exercise 03 - Heaps & Hashing
Exercise 03 - Heaps & Hashing - Solutions
Exercise 04 - Binary & Balanced Trees
Exercise 04 - Binary & Balanced Trees - Solutions
Exercise 05 - Graphs
Exercise 05 - Graphs - Solution
Exercise 06 - Dynamic Programming
Exercise 06 - Dynamic Programming - Solutions
Exercise 07 - State Space Search
Exercise 07 - State Space Search - Solution
Exercise 08 - Adversarial Search
Exercise 08 - Adversarial Search - Solution
Exercise 09 - Metaheuristic & Constrained Satisfaction
Exercise 09 - Constrained Satisfaction - Solution
Exercise 10 - Expert Systems & Numerical Optimization
Exercise 10 - Expert Systems & Numerical Optimization (Solution)
Exercise 11 - Machine Learning
L11: Graph Algorithms ►
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