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CSC311 Fall 2021 Homework 3 Homework 3 Deadline: Wednesday, Nov. 3, at 11:59pm. Submission: You will need to submit three files: • Your answers to all of the questions, as a PDF file titled hw3_writeup.pdf. You can produce the file however you like (e.g. LATEX, Microsoft Word, scanner), as long as it is readable. If […]
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Lecture 3, Part 2: Training a Classifier Roger Grosse 1 Introduction Now that we’ve defined what binary classification is, let’s actually train a classifier. We’ll approach this problem in much the same way as we did linear regression: define a model and a cost function, and minimize the cost using gradient descent. The one thing
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CSC 311: Introduction to Machine Learning Lecture 3 – Bagging, Linear Models I Roger G. of Toronto, Fall 2021 Intro ML (UofT) CSC311-Lec3 1 / 49 Copyright By PowCoder代写 加微信 powcoder Today we will introduce ensembling methods that combine multiple models and can perform better than the individual members. I We’ve seen many individual models
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CSC311 Fall 2021 Homework 2 Homework 2 Deadline: Wednesday, Oct. 13, at 11:59pm. Submission: You need to submit five files through MarkUs1: Copyright By PowCoder代写 加微信 powcoder • Your answers to Questions 1, 2, 3, and 4, as a PDF file titled hw2_writeup.pdf. You can produce the file however you like (e.g. LATEX, Microsoft Word,
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Lecture 2: Linear regression 1 Introduction Let’s jump right in and look at our first machine learning algorithm, linear regression. In regression, we are interested in predicting a scalar-valued target, such as the price of a stock. By linear, we mean that the target must be predicted as a linear function of the inputs. This
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Lecture 3, Part 1: Linear Classification 1 Introduction Last time, we saw an example of a learning task called regression. There, the goal was to predict a scalar-valued target from a set of features. This time, we’ll focus on a slightly different task: binary classification, where the goal is to predict a binary-valued target. Here
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CSC311 Fall 2021 Final Project Final Project Deadline: Friday, Dec. 3, at 11:59pm Submission: You need to submit the following files through MarkUs1: Copyright By PowCoder代写 加微信 powcoder • Your answers to Part A and B, as a PDF file titled final_report.pdf. You can produce the file however you like (e.g. LATEX, Microsoft Word, scanner),
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CRICOS code 00025BCRICOS code 00025B This course includes 13 lectures and 10 tutorial/practical sessions Copyright By PowCoder代写 加微信 powcoder Programming and Linux experiences required! Recap – Course Structure Introduction topics&appl VT: Docker I VT: Docker II Spark I DBs in Cloud Networks & Load Balancing Security & Lecture 11 Lecture 12 Lecture 10 VT: Docker
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CRICOS code 00025BCRICOS code 00025B Copyright By PowCoder代写 加微信 powcoder Cloud Computing CRICOS code 00025BCRICOS code 00025B • Apache Spark and its Characteristics • Resilient Distributed Dataset (RDD) • RDD Operations – Transform & Action • Lazy evaluation and RDD Lineage graph • Terms in Spark • Narrow and Wide Dependencies • How Spark works
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24/08/2021 CRICOS code 00025BCRICOS code 00025B Copyright By PowCoder代写 加微信 powcoder • Mask restrictions continue – carrying masks, wearing masks, check-in QLD • GCP coupons redeem (check the latest announcement) • The next Student Consultative Committee meeting will be taking place next Wednesday, 25 August. • Students can join the mailing list by emailing The