Project 2: CS61Classify Part A Deadline: Thursday, February 16, 11:59:59 PM PT Part B Deadline: Thursday, March 2, 11:59:59 PM PT In this project, you will write RISC-V assembly code to classify handwritten digits with a simple machine learning algorithm. The goal of this project is to familiarize you with RISC-V, specifically calling convention, calling […]
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Homework 6 | C88C Spring 2023 Homework 6 Due at 11:59:59 pm on Thursday, 3/9/2023. Instructions Download hw06.zip. Inside the archive, you will find starter files for the questions in this homework, along with a copy of the OK autograder. Submission: When you are done, submit with python3 ok –submit. You may submit more than once
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###################### # Required Questions # ###################### # Probably a die-re situation from operator import add, mul def reduce(reducer, seq, start): “””Reduce a sequence under a two-argument function starting from a start value. >>> def add(x, y): … return x + y >>> def mul(x, y): … return x*y >>> reduce(add, [1,2,3,4], 0) >>> reduce(mul, [1,2,3,4],
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# COMP1110/6710 Final Exam 2020 S1 The questions provided here comprise the final exam for COMP1110/6710 in Semester 1 of 2020. These are provided for you as sample questions. Notice that some questions have multiple variations, labelled ‘A’, ‘B’, etc… When you sit a real exam, you would only get one variation. _Please note that
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# COMP1110/1140/6710 2020 S2 Exam This repo contains an IntelliJ project for the 2020 S2 exam. *Note that you will see multiple versions of many of the questions (eg Q1.1A, Q1.1B, etc). In the actual exam you would be randomly assigned one of the variants. When using this as a practice exam, you should just
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Project 2A: NGordnet (NGrams) CS 61B Spring 2023 Each assignment will have an FAQ linked at the top. You can also access it by adding “/faq” to the end of the URL. The FAQ for Project 2A is located Introduction # In this project, we will build a browser based tool for exploring the history
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package ngordnet.ngrams; import java.util.Collection; * An object that provides utility methods for making queries on the * Google NGrams dataset (or a subset thereof). * An NGramMap stores pertinent data from a “words file” and a “counts * file”. It is not a map in the strict sense, but it does provide additional * functionality.
package ngordnet.ngrams; import java.util.List; import java.util.TreeMap; * An object for mapping a year number (e.g. 1996) to numerical data. Provides * utility methods useful for data analysis. * @author Josh Hug public class TimeSeries extends TreeMap { private static final int MIN_YEAR = 1400; private static final int MAX_YEAR = 2100; // TODO: Add any
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1. Overview of the Assignment Assignment 3 In Assignment 3, you will complete two tasks. The goal is to familiarize you with Locality Sensitive Hashing (LSH), and different types of collaborative-filtering recommendation systems. The dataset you are going to use is a subset from the Yelp dataset used in the previous assignments. 2. Assignment Requirements
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ECE/CS 434 MP2 Due on Monday Feb 27 11:59PM on Gradescope Objective¶ In this MP, you will: Implement DUET algorithm to separate a mixture of N voice signals from received from two microphones Problem Overview¶ Consider a problem of separating N sources ($S_1$, $S_2$, … $S_N$) from recordings on 2 microphones ($R_1$ and $R_2$). According