我最近試用了SeaSalt公司底下的SeaMeet跟SeaChat，前者可以自動記錄並摘要 Google Meet會議內容，後者則是簡單建立聊天機器人。這篇就是我報告投影片的彙整，供大家參考。
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我開發了一份Colab筆記本「內部一致性信度分析：Cronbach's Alpha計算器」，方便大家分析量表的內部一致信信度Cronbach's Alpha。這份筆記本能夠分析整份量表的Cronbach's Alpha，也可以各別計算量表中各個構面(subscaler)的Alpha係數。同時計算器還會用逐一移除題目的方式，藉由指出移除後能夠提高Cronbach's Alpha的題目，讓研究者仔細檢視量表的設計是否有改善空間。
I developed a Colab notebook titled "Internal Consistency Reliability Analysis: Cronbach's Alpha Calculator" to facilitate the analysis of a scale's internal consistency reliability using Cronbach's alpha. This notebook can analyze the Cronbach's alpha for the entire scale, as well as calculate the alpha coefficient for individual subscales. The calculator also performs item-level analysis, identifying items whose removal would increase Cronbach's alpha, allowing researchers to carefully examine and potentially improve the scale's design.
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Nextcloud的AI應用程式不能處理中文，所以我自己用Langflow整合到Nextcloud，讓大型語言模型能夠根據我在雲端硬碟裡面的內容來回答問題。這篇就講一下大致上的做法。
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使用Colab來進行資料分析時，必須要經過程式執行的動作，才能取得執行後的分析結果。以下就讓我來看看怎麽在Colab裡面執行程式。
When performing data analysis using Colab, you must execute the code to obtain the analysis results. Let's take a look at how to execute codes within Colab.
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由於之前硬碟毀損，導致我用來做AI繪圖的Stable Diffusion環境全部消失。這次乾脆全部重來，用Stable Diffusion WebUI Forge重建整個繪圖環境吧。
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在Colab分析資料是現在很常用的技巧。但要將檔案上傳到Colab中，你需要進行以下的操作。
Analyzing data in Colab is a common technique nowadays. However, to upload files to Colab, you need to perform the following steps.
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