3C健忘人 - 疑難排除不求人 - no more ask for IT help

1. Look for line of "Linux ..." in GRUB menu, change message ro to rw 2. Append "init=/usr/bin/bash " and "system.unit=multi-user.target" at the end of line of "Linux..." 3. Press Ctrl + x to reboot  # system will reboot to root mode 4. command "passwd kali"  # change kali password (default account kali) 5. command  "exec /usr/sbin/init"  # go to init for testing 6. reboot kali

1.  利用管理員身分開啟 cmd.exe終端機 2.  wmic product get name  #輸入指令 3.wmic product where "name like '%intel%'" get name,version  #輸入指令 4.  wmic product where "name like 'Intel(R) Computing Improvement Program'" call uninstall  /nointeractive  #輸入指令 @powershell 1. 用管理員開啟powershell，輸入 Get-AppxPackage -all *intel(R)* | Remove-AppPackage -AllUsers 2. 移除

 1. Dify 2. Vibe coding 3. GPT bot 4. AutoGen studio(low-code) 5. Flowise  6. LlamaFlow 7. AnythingLLM 8. AgentGPT 9. LangChain 10. NocoBase 11. APITable 12. LowCodeEngine 13. Amplication 14. Supervision 15. Node-RED 16. Refine 17. TooUet 18. Appsmith 19. n8n 20. NocoDB 21. AppFlowy 22. make.com

真陽(比)率 (True Positive Rate, TPR) - 我們所關心的事件(陽性)，被正確預測出的比例 同義詞：敏感度(sensitivity)、召回率(positive recall、recall) 真陽率=敏感度=召回率= TP / (TP + FN) . # TP: True Positive真陽, FN: false Negative假陰 假陰(比)率 (False Negative Rate, FNR) - 陽性事件中，被錯誤預測為陰性的比例： 假陰率=1-真陽率=1-(TP / (TP + FN)) = FN / (TP + FN) 真陰(比)率( True Negative Rate, TNR )  - 陰性事件中被正確預測出的比例 同義詞：特異性(specificity)、陰性召回率(negative recall) 特異性 = TN / (TN + FP ) # TN: True Negative真陰, FP: False Positive假陽 假陽(比)率 (False Positive Rate, FPR) - 陰性事件被錯誤預測為陽性的比例 假陽率 = 1- (TN / ( TN + FP )) = FP / (TN + FP) 從觀測面向轉預測面向 精確 度(precision) - 預測為陽性事件中正卻的比例、陽性率預測值(Positive Predictive Value, PPV) 精確度 = PPV = TP / ( TP + FP ) 陰性率預測值 (Negative Predictive Value, NPV) - 類別分布平衡情況下，預測為陰性的正確比例 NPV = TN / (TN + FN) 偵測率(detection rate) - 所有樣本中，陽性被確偵測出來的比例 DR = TP / ( TP + FN + TN + FP ) 普遍率(prevalence) - 該類樣本佔樣本總數的比例，以陽性為例，所有樣本中陽性事件比例為實際 陽性事件普遍率 普遍率 = (TP + FN) / (TP + FN + FP + TN)  偵測普遍率(detection prevalence) - 所有樣本中預測為陽性的比例，普遍與偵測普遍率都大於偵測率 偵測普遍率 (TP + FP) / (TP + ...

 grubby --info=ALL | grep -B1 '^kernel=' ls /boot/vmlinuz* grubby --set-default /boot/vmlinuz-4.18.0-553.45.1.el8_10.x86_64 # 58.1 downgrade 45.1 grubby --default-kernel. # to confirm  reference https://support.flashgrid.io/hc/en-us/articles/21054031806359-Downgrade-kernel-in-RHEL8

1. 選取標題 2. 選擇表格版面配置 3.點選重複標題        參考資料 https://support.microsoft.com/zh-tw/office/%E5%9C%A8%E5%BE%8C%E7%BA%8C%E9%A0%81%E9%9D%A2%E4%B8%8A%E9%87%8D%E8%A4%87%E8%A1%A8%E6%A0%BC%E6%A8%99%E9%A1%8C-2ff677e0-3150-464a-a283-fa52794b4b41 

 1. Download Creation Tool from below https://www.microsoft.com/zh-tw/software-download/windows11 2. search => cmd.exe  => run as administrator cd C:\Users\AccountName\Downloads   # if your mediacreationtool.exe in  "my computer" > "download" >media 3. In  command line mode type commands as below mediacreationtool.exe /Eula Accept /Retail /MediaArch x64 /MediaLangCode zh-TW /MediaEdition Enterprise  or mediacreationtool.exe /Eula Accept /Retail /MediaArch x64 /MediaLangCode zh-TW /MediaEdition Professional 4. download software  rweverything  from http://rweverything.com/download/ 5. 亦可直接透過網頁下載 https://www.microsoft.com/zh-tw/software-download/windows11 往下方找尋如以下圖片

 1. IF you want to download app from microsoft store but it's locked by adminstrator, 2. Go to https://https://store.rg-adguard.net and enter your app link, for instance，HEIF - https://apps.microsoft.com/detail/9pmmsr1cgpwg?hl=zh-tw&gl=TW 3. copy hyperlink abount file .appxbundle and Download from powershell on command-line wget  http://tlu.dl.delivery.mp.microsoft.com/filestreamingservice/files/7f078305-4d9a-418a-b9a8-718cef6dabc7?P1=1729585564&P2=404&P3=2&P4=VW3hnMF%2bjnXJl3AyUNJEfE%2f16Jx2t%2bp6oOXILb%2fY3VLRzAF4K8DWWoe32WyB51X8eZojWb6zsGL7rGEvGptXdA%3d%3d  -o Microsoft.HEIFImageExtension_1.1.2631.0_neutral_~_8wekyb3d8bbwe.appxbundle references https://www.makeuseof.com/download-install-msixbundle-appx-appxbundle-microsoft-store/

@以範圍區分 @以實作方式區分 統計分析：涵括貝式(Bayesian)分類、Bayesian分析 軟計算：涵括類神經網路(Artificial Neural Network)、模糊理論、基因演算   機器學習建模 1. 設定研究目 => 2. 準備資料      => 3. 使用訓練集資料建模            => 4. 測試模型                 => 5. 模型評估                      => 6. 資料驅動決策     參考資料 統計之美第二版，深智文化，2022