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Lecture Algorithms

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  • Probability and Computer science - Lecture 2: Probabilistic analysis and randomized algorithm. This lecture provides students with content including: sample space and events properties and propositions; probabilistic analysis; the hiring problem; worst-case analysis; randomized algorithm;... Please refer to the detailed content of the lecture!

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  • Probability and Computer science - Lecture 3: Basic probability - axioms, conditional probability, random variables, distributions. This lecture provides students with content including: application verifying polynomial identities; axioms of probability; analysis of the considered algorithm; notion of independence; notion of conditional probability; random variables; linearity of expectation;... Please refer to the detailed content of the lecture!

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  • Probability and Computer science - Lecture 4: Conditional probability, applications, geometric distribution. This lecture provides students with content including: application verification of matrix multiplication; application randomized min-cut; geometric distribution; coupon collector’s problem;... Please refer to the detailed content of the lecture!

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  • Lecture Artificial intelligence: k-Nearest Neighbors. This lecture provides students with content including: the kNN requires; three-class 2D problem; Euclidian distance; feature nomalization; feature weighting; computational complexity; kNN - a lazy learning algorithm;... Please refer to the detailed content of the lecture!

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  • Lecture Artificial intelligence: Perceptron learning algorithm. This lecture provides students with content including: dot product of 2 vectors; angle between 2 vectors; single perceptron;... Please refer to the detailed content of the lecture!

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  • Lecture Artificial intelligence: Q learning. This lecture provides students with content including: supervised learning; unsupervised learning; reinforcement learning; utilize the Q matrix;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 1. This lesson provides students with content about: C Programming practice in UNIX environment; programming topics related to Data Structures and Algorithms; compiler gcc;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 7. This lesson provides students with content about: binary search; algorithm; Big O Notation; complexity of search algorithm; dictionary order;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 10. This lesson provides students with content about: elementary sorting algorithm; insertion sort; selection sort; bubble sort (exchange sort); heap sort;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 11. This lesson provides students with content about: advanced sorting algorithm; quick sort; merge sort; merge algorithm; process of merge; exercises;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 12. This lesson provides students with content about: recursive functions; write a recursive algorithm; hint; improving quicksort; exercises;... Please refer to the detailed content of the lecture!

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  • Lecture C programming basic: Week 13. This lesson provides students with content about: string pattern matching algorithms; Naive algorithm; Knuth-Morris-Pratt algorithm; Boyer-Moore algorithm; exercises;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 1. This lesson provides students with content about: array, string, pointer review; character based file operations in unix; programming exercises;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 2. This lesson provides students with content about: structures, dynamic allocation review; memory image based file operations; exercises;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 3. This lesson provides students with content about: self referential structure in C; data structure “single linked LIST”; data structure “double linked LIST”;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 4+5. This lesson provides students with content about: implementation of stack using array; implementation of stack using linked list; implementation of circular queue using array; implementation of queue using linked list; exercises on stack and queue;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 6. This lesson provides students with content about: search algorithm; sequential searching; linear search; sentinel search; self organized searching; self organized list; searching arrays by linear search;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 7. This lesson provides students with content about: binary search; binary search code; recursive binary search; binary search performance test; Big O Notation; running time analysis in searching algorithms; list verification;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 8. This lesson provides students with content about: how to use debugger tool (gdb); tree data structure; binary tree; binary search tree; recursive processing on tree;... Please refer to the detailed content of the lecture!

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  • Lecture Data structure and Algorithm basic lab: Week 9. This lesson provides students with content about: how to build programs using makefile utility; tree traversal; depth first search; breadth first search; exercises;... Please refer to the detailed content of the lecture!

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