Thursday, January 11, 2018

回歸寫作初心 台灣Medium 思書

Medium 這兩年很紅,覺得很潮


SOSreader - 專為寫作者而生的集資訂閱平台

Tuesday, January 2, 2018

快速打包應用程式到QNAP NAS (QDK, QPKG)

目前我們使用github 分享 關於打包應用到QNAP NAS 請參考

下方連結為打包 app 說明文件及開發工具下載位置請參考

For a start on developing on QNAP, developers can find the related information in the following link:

In our experience, most developers are interesting in file management API and Download Station API, please refer to

If they are interesting in other API documents, please refer the index file here (

If they are plan to develop the App that running on NAS, following is the quick start guide:

- Download link of QDK for NAS

Tuesday, December 26, 2017

QuAI 機器學習開發平台登場 - QNAP NAS 就是人工智慧開發的敲門磚

更多訊息可以上FB: QuAI Community


Sunday, December 17, 2017

Binary Classification (二元分類)

Binary Classification (二元分類)

Binary or binomial classification is the task of classifying the elements of a given set into two groups (predicting which group each one belongs to) on the basis of a classification rule. Contexts requiring a decision as to whether or not an item has some qualitative property, some specified characteristic, or some typical binary classification include:

  • Medical testing to determine if a patient has certain disease or not – the classification property is the presence of the disease.
  • A "pass or fail" test method or quality control in factories, i.e. deciding if a specification has or has not been met – a Go/no go classification.
  • Information retrieval, namely deciding whether a page or an article should be in the result set of a search or not – the classification property is the relevance of the article, or the usefulness to the user.

related information:

Friday, December 15, 2017

Friday, December 8, 2017

Q: Why do we have to use Python?

Q: Why do we have to use Python? 

A: Python is an open-source language, anyone can use it from anywhere in the world. It is widely used in academics (research labs) or in the industry. It has a useful library "Numpy" that makes math operations very easy. Python has several deep learning frameworks running on top of it (Tensorflow, Keras, PaddlePaddle, CNTK, Caffe, ...) and you are going to learn some of them. It is also easy to learn. Furthermore, we believe Python has a good future, as the community is really active and builds amazing stuff.


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