Assessment 2

Assessment 2 Weighting: 45% Total marks: 40 The assessment covers the content of Week 3-6. It addresses the following learning outcome(s): • Analyse real world tasks using multi-layer perceptron neural network, ARMA/ARIMA and LSTM for classiIication and time-series prediction. • Develop and deploy multi-layer perceptron neural network, ARMA/ARIMA and LSTM in Python • Tune hyperparameters

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STAT 861: Theoretical Foundations of Machine Learning University of Wisconsin–Ma

CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 2. Due 10/27/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you

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STAT 861: Theoretical Foundations of Machine Learning University of Wisconsin–Ma

CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 0. Due 9/15/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you

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STAT 861: Theoretical Foundations of Machine Learning University of Wisconsin–Ma

CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 1. Due 10/06/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submission. 2. I recommend that you

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STAT 861: Theoretical Foundations of Machine Learning University of Wisconsin–Ma

CS/ECE/STAT-861: Theoretical Foundations of Machine Learning University of Wisconsin–Madison, Fall 2023 Homework 3. Due 11/08/2023, 11.00 am Instructions: 1. Homework is due at 11 am on the due date. Please hand over your homework at the beginning of class. Please see the course website for the policy on late submissions. 2. I recommend that you

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CS861: Theoretical Foundations of Machine Learning Lecture 5 09 15 2023 Univer

CS861: Theoretical Foundations of Machine Learning Lecture 5 – 09/15/2023 University of Wisconsin–Madison, Fall 2023 Lecture 05: Growth Function and VC Dimension Lecturer: Kirthevasan Kandasamy Scribed by: Chenghui Zheng, Yixuan Zhang Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with

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