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computational-method-for-data-analysis-

cse415-introduction-to-artificial-intelligence

Course description: Artificial intelligence is a broad field encompassing computational models of human cognition, formal systems for representing and processing symbolic information, expert systems technology, and a variety of techniques for learning, understanding signals, and solving problems. This course provides a basic introduction to key techniques: state-space search, game-playing, probabilistic reasoning, and learning. Over the last 50 years the field has grown tremendously, and this course can only scratch the surface within the field. This course begins with a discussion of what "artificial intelligence" means and how it can be useful. Next is a grounding in state-space search, problem formulation and solving. We then consider state-space search in the context of game playing, which then leads to alpha-beta pruning, expectimax search and the modeling of uncertainty. After that, we focus primarily on machine learning, starting with methods for reasoning under uncertainty. We cover learning of decision trees from examples, reinforcement learning in Markov Decision Processes, perceptron learning, and deep learning. We touch briefly on the future of AI. The teaching methodology combines lectures, in-class and out-of-class exercises, and programming assignments.

data-structure-and-algorithm-

sorting and searching, divide and conquer, greedy algorithms, dynamic programming. Data structure : stack and queue, priority queue, binary tree, Doubly-Linked Lists,Dynamic Arrays and Amortized Analysis, Hash Tables ... etc.

dmdpack

Dynamic Mode Decomposition

fast_principalcurvessurfaces

This is a fast PCS code implemented by James McQueen and me.

gesturebaseduiproject

high-perfomance-computing

Computation and simulation are increasingly important in all aspects of science and engineering. At the same time writing efficient computer programs to take full advantage of current computers is becoming increasingly difficult. Even laptops now have 4 or more processors, but using them all to solve a single problem faster often requires rethinking the algorithm to introduce parallelism, and then programming in a language that can express this parallelism. Writing efficient programs also requires some knowledge of machine arithmetic, computer architecture, and memory hierarchies.

lc

lectures

Notes, slides, and code from the in-class lectures.

leetcode-solution-code

megaman

megaman: Manifold Learning for Millions of Points

musicnotationrecongnitionsystem

Ongoing project aiming to build a big project within 4 months that emphasizes the GUI - the Graphical User Interface and pattern recognition. We will build a gesture based music notation system.

opencv

Open Source Computer Vision Library