Image embedding through deep neural networks.Inputs
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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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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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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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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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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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DeepMind Technologies is a UK-based AI company. It was founded in 2010 by Demis Hassabis, Shane Legg and Mustafa Suleyman, and was acquired by Google in 2014 for £400 million so it is now part o
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https://techcrunch.com/2019/06/27/mits-new-interactive-machine-learning-prediction-tool-could-give-everyone-ai-superpowers/Soon, you might not need anything more specialized than a readily accessible touchscreen device and any existing data sets you have access to in order to build powerful prediction tools. A new experiment from MIT and Brown Universityresearchers have added a capability to their ‘Northstar’ interactive data system that can “instantly generate machine-learning models” to use with their exiting data sets in order to generate useful predictions.
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REF: https://udn.com/news/story/6871/3537183人工智慧在大型國際企業裡的應用，包含產品、流程和宣傳三個層面。在產品和服務方面，企業可以利用AI 打造用戶的黏著度，提升軟硬體產品及服務的競爭力；流程方面，通過AI的優化與規劃，可改善製造、CRM、物流、營銷等各方面流程，有效降低企業成本；最後則是AI的宣傳效果，通過AI產品可提高企業及品牌感知度，甚至提振公司股價。觀察大陸市場的營運狀況可發現，除了聯想之外，Google、微軟、百度、騰訊、蘋果、華為、小米、IBM等國際大公司都在積極布局人工智慧，以協助公司變革轉型。
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https://www.kdnuggets.com/2018/05/general-approaches-machine-learning-process.htmlI actually came across Guo's article by way of first watching a video of his on YouTube, which came recommended after an afternoon of going down the Google I/O 2018 video playlist rabbit hole. The post is the same content as the video, and so if interested one of the two resources will suffice.
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