代寫AIML 2023-2024 Coursework

            時間:2024-03-17  來源:  作者: 我要糾錯


            AIML 2023-2024 Coursework
            March 12, 2024
              Figure 1: Convolutional neural network for coursework assignment.
            Problem The goal of this take-home assignment is to implement, in Python, a simple two-layer convolutional neural network (CNN) with five inputs x1, . . . , x5, four hidden nodes z1, . . . , z4 and one output y with ReLU activations, according to the diagram shown in Figure 1. The hidden layer and output of the CNN is to be computed along with the gradient of the hidden layer and output with respect to parameter w1. The values oftheparameterswillbew1 =1.2,w2 =−0.2,v1 =−0.3,v2 =0.6,v3 =1.3andv4 =−1.5.
            Instructions The CNN implementation is to be computed using a single Python function in single Python file. The interface to the function should be in the precise format,
            y, z = convnet(x) (1)
            where x = [x1, x2, x3, x4, x5] is a list of five numerical inputs (for example, a set of real numbers x=[0.3,−1.5,0.7,2.1,0.1]), and it should return the value of y as a number of the type dual and, z=[z1,z2,z3,z4] as a list of four numbers of type dual defined in the course code module ad.py. Therefore, when testing, you should expect to import this module. The implementation should use the specific values of the weight parameters given above.
            Submission TopreparethePythoncodefileforsubmission,itmustbenamedintheformatinitials_studentid.py, for instance if your initials are ’AJD’ and your ID is 5716631 then your file should be named ajd_5716631.py. Submit the file through the Assignments page on Canvas. The deadline for submissions is 12pm UK time, 21st March 2024.
            Marking The function will be marked automatically by calling it inside Python, and checking the results against a model solution. A fully correct solution will receive 20 marks. A solution which has a partially correct
            請加QQ:99515681  郵箱:99515681@qq.com   WX:codehelp 

            標簽:

            掃一掃在手機打開當(dāng)前頁
          1. 上一篇:代寫COMP3411/9814 Bridge Puzzle編程代做
          2. 下一篇:COMP2207 代做、R 程序設(shè)計代寫
          3. 無相關(guān)信息
            昆明生活資訊

            昆明圖文信息
            蝴蝶泉(4A)-大理旅游
            蝴蝶泉(4A)-大理旅游
            油炸竹蟲
            油炸竹蟲
            酸筍煮魚(雞)
            酸筍煮魚(雞)
            竹筒飯
            竹筒飯
            香茅草烤魚
            香茅草烤魚
            檸檬烤魚
            檸檬烤魚
            昆明西山國家級風(fēng)景名勝區(qū)
            昆明西山國家級風(fēng)景名勝區(qū)
            昆明旅游索道攻略
            昆明旅游索道攻略
          4. NBA直播 短信驗證碼平臺 幣安官網(wǎng)下載 歐冠直播 WPS下載

            關(guān)于我們 | 打賞支持 | 廣告服務(wù) | 聯(lián)系我們 | 網(wǎng)站地圖 | 免責(zé)聲明 | 幫助中心 | 友情鏈接 |

            Copyright © 2025 kmw.cc Inc. All Rights Reserved. 昆明網(wǎng) 版權(quán)所有
            ICP備06013414號-3 公安備 42010502001045

            主站蜘蛛池模板: 久久久久人妻一区二区三区| 亚洲精品色播一区二区| 国产精品 一区 在线| 人妻夜夜爽天天爽一区| 亚洲国产一区二区三区在线观看| 亚洲国产综合精品中文第一区| 国产在线视频一区| 无码精品人妻一区二区三区人妻斩 | 后入内射国产一区二区| 亚洲成人一区二区| 久久一区二区三区精品| 国产情侣一区二区| 国产精品无码AV一区二区三区| 日本激情一区二区三区| 国产精品日韩欧美一区二区三区 | 内射一区二区精品视频在线观看| 国产乱码一区二区三区四| 波多野结衣一区二区免费视频| 国产一区二区草草影院| 国产福利一区二区三区在线视频 | 亚洲国产综合无码一区二区二三区 | 88国产精品视频一区二区三区| 精品久久久久久中文字幕一区| 国产AV午夜精品一区二区三| 国产精品乱码一区二区三| 丰满岳乱妇一区二区三区| 精品人妻系列无码一区二区三区| 国产一区二区三区在线观看免费| 久久一区二区明星换脸| 一区二区三区免费视频网站| 亚洲蜜芽在线精品一区| 国产乱码精品一区二区三| 亚洲AV成人一区二区三区AV| 日本在线视频一区| 亚洲日韩国产一区二区三区在线 | 久久成人国产精品一区二区| 一区二区在线视频免费观看| 精品一区二区三区视频在线观看| 久久久不卡国产精品一区二区 | 日本一区二区在线免费观看| 中文字幕日本精品一区二区三区 |