ml
US
・UK
A2 初級
n.名詞毫升
Your brother needs to drink 5 ml of medicine every six hours
影片字幕
你會跟高登·拉姆齊一起煮這些食譜嗎？| 頂級廚房| 高登·拉姆齊 (Can YOU Cook These Recipes With Gordon Ramsay? | Next Level Kitchen | Gordon Ramsay)
- First off, 200 ml of coconut milk.
好的，放進去。
- First off, 200 ml of coconut milk.
這根本就像是漂亮的裝飾。
烈酒的標準飲用方式是什麼？ (What are the standard serves of spirits)
- and also must deliver fixed quantities of 15 ml, 30 ml, or 60 ml.
倒入烈性酒，直至半月板與搖酒器頂部持平或達到柱狀線。3.
- and also must deliver fixed quantities of 15 ml, 30 ml, or 60 ml.
倒入烈性酒，直至半月板與搖酒器頂部持平或達到柱狀線。3.
大型語言模型入門教學！ (Introduction to large language models)
- In ML, parameters are often called hyperparameters.
在 ML 中，參數通常被稱為超參數。
- In ML, parameters are often called hyperparameters.
產生這一想法有兩個原因。
Jerry Liu (LlamaIndex)：打造真正自動化知識工作的 AI Agent！ (Building AI Agents that actually automate Knowledge Work - Jerry Liu, LlamaIndex)
- If in contrast to more traditional techniques where you use kind of like hand-tuned and task-specific ML models to achieve kind of like document parsing over a specific class of documents, LLMs actually have a much general layer of accuracy that you can use to your advantage in just like understanding and inhaling any type of document with any type of complexity.
與傳統技術相比，在傳統技術中，你需要使用經過人工調整的、針對特定任務的 ML 模型來實現對特定類別文檔的解析，而 LLM 實際上具有更廣泛的準確性，你可以利用它的優勢來理解和吸入任何類型、任何複雜程度的文檔。
- Um, if, uh, in contrast to more traditional techniques where you use kind of like hand-tuned and task-specific ML models to achieve, uh, kind of like document parsing over a specific class of documents, LLMs actually have a much general layer of accuracy, um, that you can use to your advantage in just like understanding and inhaling any type of document with, uh, any type of complexity.
但法學碩士們一直沒有解決這個問題。
AI工程師入門：最真實的學習地圖！👩💻🚀 (AI Engineering: A Realistic Roadmap for Beginners)
- I have all kinds of Python roadmaps out there, but the point is you're probably going to have to spend at least two months here, learning Python, getting good at it, and just learning standard software engineering with Python before we can dive into AI and ML.
我有各種 Python 路線圖，但重點是，在我們深入研究人工智能和 ML 之前，你可能至少要花兩個月時間在這裡，學習 Python，熟練掌握 Python，並用 Python 學習標準的軟件工程。
- and just learning standard software engineering with Python before we can dive into AI and ML.
第一種是 Git 和 GitHub，用於版本控制，本質上是保存和檢查點你的代碼。
