本次分享的實境技術主題,將探討虛擬實境(VR)與擴增實境概念(AR)與實現的工具,並說明專屬與非專屬開發平台及開發工具串聯的分工,可以快速掌握實境技術的趨勢與開發方式。
This topic shares you with reality technology, including virtual reality (VR) and augmented reality (AR). This topic also includes the developed tools used in a specific or non-specific platform. Through this topic, you can catch the trend of reality technology.
This document discusses the evolution of deep learning models for natural language processing tasks from RNNs to Transformers. It provides an overview of sequence-to-sequence models, attention mechanisms, and how Transformer models use multi-head attention and feedforward networks. The document also covers BERT and how it represents language by pre-training bidirectional representations from unlabeled text.
Kubernetes Basis: Pods, Deployments, and ServicesJian-Kai Wang
Kubernetes is a container management platform and empowers the scalability to the container. In this repository, we address the issues of how to use Kubernetes with real cases. We start from the basic objects in Kubernetes, Pods, deployments, and Services. This repository is also a tutorial for those with advanced containerization skills trying to step into the Kubernetes. We also provide several YAML examples for those looking for quickly deploying services. Please enjoy it and let's start the journey to Kubernetes.
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This document discusses the evolution of deep learning models for natural language processing tasks from RNNs to Transformers. It provides an overview of sequence-to-sequence models, attention mechanisms, and how Transformer models use multi-head attention and feedforward networks. The document also covers BERT and how it represents language by pre-training bidirectional representations from unlabeled text.
Kubernetes Basis: Pods, Deployments, and ServicesJian-Kai Wang
Kubernetes is a container management platform and empowers the scalability to the container. In this repository, we address the issues of how to use Kubernetes with real cases. We start from the basic objects in Kubernetes, Pods, deployments, and Services. This repository is also a tutorial for those with advanced containerization skills trying to step into the Kubernetes. We also provide several YAML examples for those looking for quickly deploying services. Please enjoy it and let's start the journey to Kubernetes.
Tensorflow Extended: 端至端機器學習框架: 從概念到實作 (Tensorflow Extended: An end-to-end ML...Jian-Kai Wang
Tensorflow Extended (TFX) 為一端至端的機器學習框架。內容介紹 TFX 架構概念與各組成函式庫,並藉由預測結構化資料與非結構圖像辨識作為範例進行實作。
Tensorflow Extended (TFX) is an end-to-end ML pipeline framework. This tutorial introduces you to the concept of TFX and guides you on how to implement the whole process from scratch.
從圖像辨識到物件偵測,進階的圖影像人工智慧 (From Image Classification to Object Detection, Advance...Jian-Kai Wang
複習及補充機器學習與深度學習,說明物件偵測要解決的問題。
探討策略1: One-Shot Solution,舉 YOLO 為例及其 Hands-On 操作,並探討其他相關演算法與其發展;其次探討策略2: Divide-and-Conquer,以 Faster RCNN 為例與利用 Tensorflow Object Detection API 進行練習,探討其他相關演算法與其發展。
最後探討增進訓練結果與演算法發展,並介紹機器學習的推論與應用與應用機器學習導入產業。
We first reviewed the Machine Learning basis, introduced what object detection is, and then described what the problems it is going to solve. (both the localization and the category issues)
Second, we introduced two types of algorithms that represent two different ideas. One is a One-Shot solution and the other is a divide-and-conquer way. The representative algorithm for the one-shot solution is "YOLO" and the other one is "Faster R-CNN". We also implemented the whole YOLO training and inference processes from scratch via Tensorflow 2.0. On the other hand, we introduced how to use Tensorflow Object Detection APIs to implement the whole Faster R-CNN training and inference processes.
Third, we quickly introduced the evolution of several famous object detection algorithms and how to improve training performance and results.
In the final, we introduced the gap between the AI industrial in research and in practice.
使用 Keras, Tensorflow 進行分散式訓練初探 (Distributed Training in Keras and Tensorflow)Jian-Kai Wang
從設計架構到實作方式,帶大家進入高效模型訓練。
開源程式碼 : https://github.com/jiankaiwang/distributed_training
From designing architecture to implementation scripts, guide you beginning a high-efficiency way in training deep learning models.
Source Code: https://github.com/jiankaiwang/distributed_training
2017 更新版 : 使用 Power BI 資料分析工具於傳染病應用 (Power BI Platform for Communicable Disea...Jian-Kai Wang
以 Open Data 為對象透過 Power BI 分析傳染病疫情,並以此為主軸介紹 Power BI 服務及其分析流程。使用資料為歷年健保門診類流感就診人次與健保門診及住院就診人次統計-腸病毒。
包含 : Power BI 概念與架構, 使用 Power BI 存取雲端數據, 使用 Power BI 建置資料模型, 開發視覺化互動性分析報表, 與使用行動裝置存取 Power BI。
此文件以 2017 Power BI 作為操作平台。
Use Power BI platform to analyze open data for communicable diseases. Furthermore, introduce Power BI platform and its analyzing concept. The data demonstrated includes (1) out-patient clinicis for influenza, (2) out-patient clinicis for entrovirus.
The content includes (1) the architecture and analyzing concept, (2) access to web/local data, (3) construct data model, (4) develop interactive dashboard, and (5) access the Power BI service by mobile devices.
The document is written on the 2017 Power BI platform.
自動化資料準備供分析與視覺化應用 : 理論與實作 (automatic data preparation for data analyzing and v...Jian-Kai Wang
本文件以建立自動化資料準備供分析與視覺化應用為核心,並以 Microsoft 工具 (Excel, Access, SQL Server)、批次檔 (Python / R 作為主體) 與數項相關工具進行實作。
資料準備包含 csv, txt, json, xml 及其延伸 geojson, kml 等做為資料分析與視覺化之實作格式,並介紹 Data API 設計。
本文件並以 Open Data 與地理資訊作為使用端應用說明。
The topics to the document are related with automatic data preparation for data analyzing and visualizing. In the document, we used MS tools (Excel, Access, SQL Server), the windows batch execution (based on python / R) and other related tools to implement topics.
We deliver how to prepare the data in csv, txt, json, xml and their extension geojson and kml formats, and to introduce the web data api as well.
We also introduce some applications, including open data and GIS.
自動化系統建立 : 理論與實作 (Automatic Manufacturing System in Data Analysis)Jian-Kai Wang
本文件以建立自動化資料分析為核心,並以 Microsoft Office Excel 與 Python / R 為工具進行實作。
本完整課程建議以 6 小時以上進行授課。
The document provided you the knowledge of automatic manufacturing system in data analysis. The tool demonstrated in the document included Microsoft Office Excel and Rython / R (programming languages).
Six-hour teaching is suggested for the class.
CKAN : 資料開放平台技術介紹 (CAKN : Technical Introduction to Open Data Portal)Jian-Kai Wang
以「技術背景」,「CKAN 架構」,「客製化模版與模組」與「客製化頁面與語言轉換」等四大主軸介紹臺灣疾管署開放資料平台採用之 CKAN 系統架構。
平台 : https://data.cdc.gov.tw
日期 : 2016/09/02
The content consists of (1) background of system operations, (2) the architecture of ckan, (3) customized module and template, (4) customized pages and language translation.
Platform : https://data.cdc.gov.tw
Date : 09/02/2016
疾病管制署資料開放平台介紹 (Introduction to Taiwan Centers for Disease Control Open Data P...Jian-Kai Wang
以「開放資料 : 為甚麼開放資料?」,「開放資料類型 : 什麼資料應該開放?」,「資料準備 : 資料準備3原則」與「疾管署開放資料平台 : 打造開放、透明、完整的資料平台」等四大主軸貫穿內容。
平台 : https://data.cdc.gov.tw
日期 : 2016/09/01
The content includes
(1) Open Data : Why open data ?
(2) Types of Open Data : What kinds of data is good for open. (3) Preparation for Open Data : Rules for preparing open data.
(4) The Open Data Portal for TCDC : Develop a open, transparent and integrated open data platform.
Platform : https://data.cdc.gov.tw/en
Date : 09/01/2016
Power BI 工具於傳染病應用 (Power BI Platform for Communicable Diseases)Jian-Kai Wang
以 Open Data 為對象透過 Power BI 分析傳染病疫情,並以此為主軸介紹 Power BI 服務及其分析流程。使用資料為歷年健保門診類流感就診人次與健保門診及住院就診人次統計-腸病毒。
包含 : Power BI 概念與架構, 使用 Power BI 存取雲端數據, 使用 Power BI 建置資料模型, 開發視覺化互動性分析報表, 與使用行動裝置存取 Power BI。
日期 : 2016/06/02
Use Power BI platform to analyze open data for communicable diseases. Furthermore, introduce Power BI platform and its analyzing concept. The data demonstrated includes (1) out-patient clinicis for influenza, (2) out-patient clinicis for entrovirus.
The content includes (1) the architecture and analyzing concept, (2) access to web/local data, (3) construct data model, (4) develop interactive dashboard, and (5) access the Power BI service by mobile devices.
Date : 06/02/2016
5. Virtual reality (VR)
typically refers to computer technologies
that use virtual reality headsets to
generate the realistic images, sounds and
other sensations that replicate a real
environment or create an imaginary setting.
-Wikipedia (2017)
5
22. 22
擬真的 AR (Argumented Reality)
• 擴增實境 : 虛擬元件於實際空間
• 你我身邊的 AR 應用
• AR 抽象化
• AR 技術分類
• AR 趨勢與臺灣產業生態系
23. Argumented Reality (AR) 23
is a live direct or indirect view of a physical,
real-world environment whose elements are
"augmented" by computer-generated or extracted
real-world sensory input such as sound, video,
graphics or GPS data.
- Wikipedia (2017)
24. Google AR 眼鏡 24
https://www.youtube.com/watch?v=IZdkIVS53Uw
http://www.menshealth.com/guy-wisdom/augment-your-reality (2017)
31. Mixed Reality (MR)
31
referred to as hybrid reality, is the
merging of real and virtual worlds to
produce new environments and
visualizations where physical and
digital objects co-exist and interact in
real time.
- Wikipedia (2017)