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Position: 吳俊逸 > Latest Articles
by 吳俊逸 2019-12-27 09:47:46, Reply(0), Views(933)
Preprocesses corpus with selected methods.Inputs
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by 吳俊逸 2019-12-27 09:22:00, Reply(0), Views(1016)
Image embedding through deep neural networks.Inputs
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by 吳俊逸 2019-11-01 12:48:19, Reply(0), Views(905)
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(1297)
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(1214)
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(1157)
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(2696)
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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by 吳俊逸 2019-09-03 12:35:37, Reply(0), Views(1915)
REF: https://buzzorange.com/techorange/2019/09/01/salary-of-data-analyst/?utm_source=feedburner&utm_medium=email&utm_campaign=Feed%3A+techorange+%28TechOrange%29自 2012 年起,一直被稱為「最性感的工作」的數據科學家職位,吸引了大批遠渡重洋到達矽谷,做著「數據夢」的留學生們。
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by 吳俊逸 2019-08-27 10:21:25, Reply(0), Views(911)
本文作者:Michael Rau,科睿唯安智慧財產技術服務總監,美國註冊專利律師
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by 吳俊逸 2019-08-25 14:40:25, Reply(0), Views(1168)
人工智慧:如何以電腦解決問題1950 年代的電腦科學方起步,從科學家到一般大眾都對於電腦充滿無盡的想像,不但從大導演弗裡茨・朗的《大都會》到作家艾西莫夫的機器人三大法則,主流科學界也都預估,約莫 20 到 30 年左右的時間便可以成功創造出與人類同樣高度的人工智慧。
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