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189 Algorithms Training Courses (Page 6)

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Algorithms, Part II

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Baker Professor of Computer Science at Princeton, where he was the founding chair of the Department of Computer Science. He received the Ph.D. degree from Stanford University, in 1975. Prof. Sedgewick also served on the faculty at…

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Algorithms: Design and Analysis, Part 1

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In this course you will learn several fundamental principles of algorithm design: divide-and-conquer methods, graph algorithms, practical data structures, randomized algorithms, and more. About the Course In this course you will l…

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Algorithms: Design and Analysis, Part 2

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In this course you will learn several fundamental principles of advanced algorithm design: greedy algorithms and applications; dynamic programming and applications; NP-completeness and what it means for the algorithm designer; the…

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Advanced Trading Algorithms

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You will be taught how to differentiate between mere data mining and results based on solid empirical or theoretical foundation. Next, you will learn the ways and means of back testing the results and subjecting the back test resu…

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Cluster Analysis in Data Mining

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Created by: University of Illinois at Urbana-Champaign Taught by: Jiawei Han, Abel Bliss Professor Department of Computer Science Basic Info Course 5 of 6 in the Data Mining Specialization Language English How To Pass Pass all gra…

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Discrete Optimization

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This class teaches you how to solve complex search problems with discrete optimization concepts and algorithms, including constraint programming, local search, and mixed-integer programming. Optimization technology is ubiquitous i…

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Data-driven Astronomy

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In this course you will investigate the challenges of working with large datasets: how to implement algorithms that work; how to use databases to manage your data; and how to learn from your data with machine learning tools. The f…

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Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course)

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stack processing, parsing, code generation, and classical algorithms and data structures for memory management, vector graphics, input-output handling, and various other topics that lie at the very core of every modern computer sy…

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Neural Networks for Machine Learning

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We'll emphasize both the basic algorithms and the practical tricks needed to get them to work well. About the Course Neural networks use learning algorithms that are inspired by our understanding of how the brain learns, but they …

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Kinematics: Describing the Motions of Spacecraft

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The course ends with a look at static attitude determination, using modern algorithms to predict and execute relative orientations of bodies in space. After this course, you will be able to... * Differentiate a vector as seen by a…

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Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

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- Be able to effectively use the common neural network "tricks", including initialization, L2 and dropout regularization, Batch normalization, gradient checking, - Be able to implement and apply a variety of optimization algorithm…

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Statistical Mechanics: Algorithms and Computations

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Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach. Created by: École normale supérieure Taught by: Werner Krau…

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Computer Vision: The Fundamentals

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In this course, we will study the concepts and algorithms behind some of the remarkable successes of computer vision - capabilities such as face detection, handwritten digit recognition, reconstructing three-dimensional models of …

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Algorithmic Thinking (Part 2)

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As the central part of the course, students will implement several algorithms in Python that incorporate these techniques and then use these algorithms to analyze two large real-world data sets. The main focus of these tasks is to…