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by 吳俊逸 2020-01-01 15:29:03, Reply(0), Views(34)
簡單來說,就是協助企業客戶導入AI 技術。根據維基百科上〈Technology evangelist〉條目的定義,技術傳教士熱衷之事,在於嘗試建立起某技術的群眾效應(Critical mass),也就是讓該技術能達到足夠自我維持且持續成長的動能。就表面而言,達到行銷某技術是其任務與目的,然而就本質而言,他們是試著將自己對技術的熱愛、感動、經驗等傳播出去,不僅是讓更多人接受該技術,而是更發自內心地喜愛,甚至讓更多人自發性地將技術再推廣出去。技術傳教士影響著一群人,並讓這群人影響更多的人。必須持續精進技術能力「技術傳教士是有技術能力的人。可是他不是純做工程師,而是到社群跟其他軟體開發者交流、溝通。」
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by 吳俊逸 2019-12-30 18:23:58, Reply(0), Views(37)
We use the visual programming toolbox Orange3 to simplify image analysis by integrating deep learning embedding, machine learning procedures, and data visualization.  Orange supports the
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by 吳俊逸 2019-12-27 09:52:37, Reply(0), Views(40)
A multi-layer perceptron (MLP) algorithm with backpropagation.Inputs
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by 吳俊逸 2019-12-27 09:47:46, Reply(0), Views(33)
Preprocesses corpus with selected methods.Inputs
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by 吳俊逸 2019-12-27 09:22:00, Reply(0), Views(36)
Image embedding through deep neural networks.Inputs
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by 吳俊逸 2019-11-01 12:48:19, Reply(0), Views(96)
REF: http://www.saint-island.com.tw/TW/Knowledge/Knowledge_Info.aspx?IT=Know_1_1&CID=543&ID=13191943年,神經網路的誕生揭開了人工智慧(以下簡稱AI)的序幕。在AI發展
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by 吳俊逸 2019-10-31 16:36:28, Reply(0), Views(78)
EPO Requirements for AI PatentsGeneral Software PatentsArticle 52 of the European Patent Convention describes patentable inventions, and (in paragraph 2) specific exclusions:
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by 吳俊逸 2019-10-13 15:59:00, Reply(0), Views(85)
REF: https://www.zhihu.com/question/23946233讲讲在Google内部这三个职位的区别:
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by 吳俊逸 2019-10-13 15:38:18, Reply(0), Views(75)
REF: https://www.datacamp.com/community/blog/data-scientist-vs-data-engineerThe differences between data engineers and data scientists explained: responsibilities, tools, languages, job outlook, salary, etc.The discussion about the data science roles is not new (remember the Data Science Industryinfographic that DataCamp brought out in 2015): companies' increased focus on acquiring data science talent seemed to go hand in hand with the creation of a whole new set of data science roles and titles. And two years after the first post on this, this is still going on! 
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by 吳俊逸 2019-10-13 15:36:12, Reply(0), Views(135)
REF: https://taweihuang.hpd.io/2017/12/22/logreg101/邏輯迴歸通常是在學分類問題 (classification) 第一個會接觸到的模型,用來建立「二元目標變數」(Binary Output Variable) 跟解釋變數之間的關係,模型形式如下:
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