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CS计算机代考程序代写 deep learning algorithm matlab COMP3308/3608 Artificial Intelligence

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COMP3308/3608 Artificial Intelligence Week 9 Tutorial exercises Multilayer Neural Networks 2. Deep Learning. Exercise 1. Backpropagation (Homework) a) Show that the derivative of the hyperbolic tangent sigmoid is 1-a2. b) Write the weight change rule for this function, using the result from a). See slide 26 from the lecture on backpropagation. for an output neuron […]

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CS计算机代考程序代写 database AI prolog data mining matlab Java deep learning python Bayesian algorithm Bayesian network COMP3308/COMP3608, Lecture 1

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COMP3308/COMP3608, Lecture 1 ARTIFICIAL INTELLIGENCE Introduction to Artificial Intelligence Irena Koprinska Reference: Russell and Norvig, ch. 1 [ch. 2, ch. 26 – optional] Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 1, 2021 1 Outline • Administrative matters • Course overview • What is AI? • A brief history • The state of the art Irena Koprinska,

CS计算机代考程序代写 database AI prolog data mining matlab Java deep learning python Bayesian algorithm Bayesian network COMP3308/COMP3608, Lecture 1 Read More »

CS计算机代考程序代写 algorithm COMP3308/COMP3608, Lecture 3b

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COMP3308/COMP3608, Lecture 3b ARTIFICIAL INTELLIGENCE Local Search Algorithms Reference: Russell and Norvig, ch. 4 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 3b, 2021 1 • Optimisation problems • Local search algorithms • Hill-climbing • Beam search • Simulatedannealing • Geneticalgorithms Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 3b, 2021 2 Outline Optimisation Problems • Problem setting so

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CS计算机代考程序代写 data mining algorithm COMP3308/3608, Lecture 10a

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COMP3308/3608, Lecture 10a ARTIFICIAL INTELLIGENCE Support Vector Machines Reference: Russell and Norvig, pp. 744-748 Witten, Frank, Hall and Pal, ch.7.2, pp. 224-227 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 10a, 2021 1 Outline • Maximum margin hyperplane • Linear SVM with hard margin • Linear SVM with soft margin • Nonlinear SVM Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608

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CS计算机代考程序代写 Excel data structure algorithm COMP3308/COMP3608, Lecture 2

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COMP3308/COMP3608, Lecture 2 ARTIFICIAL INTELLIGENCE Problem Solving and Search. Uninformed Search: BFS, DFS, UCS and IDS Informed Search: Greedy Best-First Reference: Russell and Norvig, ch. 3 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 2, 2021 1 Reminders • Tutorials start this week • All tutorials will be on Zoom live-streamed • There are 2 on Tuesday

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CS计算机代考程序代写 algorithm COMP3308/COMP3608, Lecture 3a

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COMP3308/COMP3608, Lecture 3a ARTIFICIAL INTELLIGENCE A* Algorithm Reference: Russell and Norvig, ch. 3 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 3a, 2021 1 Outline • A* search algorithm • How to invent admissible heuristics Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 3a, 2021 2 A* Search • UCS minimizes the cost so far g(n) • GS minimizes

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CS计算机代考程序代写 flex decision tree algorithm information theory COMP3308/3608, Lecture 7

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COMP3308/3608, Lecture 7 ARTIFICIAL INTELLIGENCE Decision Trees Reference: Witten, Frank, Hall and Hall: ch.4.3 and ch.6.1 Russell and Norvig: p.697-707 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 7, 2021 1 Outline Core topics: • Constructing decision trees • Entropy and information gain • DT’s decision boundary Additional topics: • Avoiding overfitting by pruning • Dealing with

CS计算机代考程序代写 flex decision tree algorithm information theory COMP3308/3608, Lecture 7 Read More »

CS计算机代考程序代写 database AI data mining data science decision tree data structure DNA algorithm COMP3308/3608, Lecture 5

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COMP3308/3608, Lecture 5 ARTIFICIAL INTELLIGENCE Introduction to Machine Learning. K-Nearest Neighbor. Rule-Based Algorithms: 1R Reference: Russell and Norvig, p.693-697, 738-741 Witten, Frank, Hall and Pal, ch. 1-2, ch.4: p.91-96, 135-141 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 5, 2021 1 Outline • Introduction to Machine Learning (ML) • What is learning and ML? • Classification of

CS计算机代考程序代写 database AI data mining data science decision tree data structure DNA algorithm COMP3308/3608, Lecture 5 Read More »

CS计算机代考程序代写 database deep learning AI algorithm COMP3308/COMP3608, Lecture 4

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COMP3308/COMP3608, Lecture 4 ARTIFICIAL INTELLIGENCE Game Playing Reference: Russell and Norvig, ch. 5 Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 4, 2021 1 • Games • Characteristics • Games as search • Games of perfect information • Minimax • Alpha-beta pruning • Games of imperfect information • Games of chance Outline Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI,

CS计算机代考程序代写 database deep learning AI algorithm COMP3308/COMP3608, Lecture 4 Read More »

CS计算机代考程序代写 deep learning AI Keras data mining matlab Excel GPU algorithm COMP3308/3608, Lecture 9b

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COMP3308/3608, Lecture 9b ARTIFICIAL INTELLIGENCE Deep Learning Tutorials on Deep Learning: 1) http://cs.stanford.edu/~quocle/tutorial1.pdf 2) http://cs.stanford.edu/~quocle/tutorial2.pdf 3) http://deeplearning.stanford.edu/tutorial/ Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 9b, 2021 1 Outline • What is deep learning? • Autoencoder neural networks • Convolutional neural networks • Applications Irena Koprinska, irena.koprinska@sydney.edu.au COMP3308/3608 AI, week 9b, 2021 2 What is Deep Learning?

CS计算机代考程序代写 deep learning AI Keras data mining matlab Excel GPU algorithm COMP3308/3608, Lecture 9b Read More »