關於 data science images ，我們在網路上蒐集到這些相關的討論、資訊與評價

［台灣創業家 矽谷創業沙龍聚會］ 最年輕創業家才21歲！手機控制的隨身攜帶針灸、跟著你跑的自拍機器人、區塊鏈的搜尋引擎、測全身尺寸虛擬實境試衣服技術、攝影師作品國外圖庫變現平台

數位時代 數位時代 創業小聚 Meet Startup

BiiLabs | Provide DLT/Blockchain-as-a-Service solutions to enable the IoT-based data marketplace. 使用區塊鏈的互聯網平台

TG3D Studio| Scanatic for Fashion /Provide one-stop 3D digitization tools and data analytics service to empower fashion brands & industry achieve the vision of "Fashion on demand". 讓服飾零售的顧客掃描全身尺寸，推薦什麼牌子買什麼尺寸的科技 TG3D Studio

Heimavista| Live broadcast robot - Core Chip Module, device that requires the phone to release hands: Selfie, live broadcast, self-recording, video conference. 跟著你轉動的自拍旋轉器

ATGENOMIX | Atgenomix is changing bioinformatics and data analysis market by providing machine learning-powered sequencing, cloud and open source computing, and AI genomics into an enterprise and scalable Bio-IT platform. 人工智慧生物科技數據平台

xMight| xMight is an energy aggregator; provide renewable energy, energy storage and EV charging integration management service. 讓電動車充電站更省錢更安全

LUFTQI|Solutions for Allergy Sufferers. Luft Cube Personal Air purifier helps decomposing VOCs, orders, bacterial, virus, and mold. Luft Cube just need no filters, powered by USB, 2 USD/year electricity bill. 隨身帶的空氣清新器（阿雅：是不是可以不用再怕身邊的人偷放屁？哈）

KryptoGo|KryptoGO organizes blockchain information, to make blockchain more accessible to everyone and helps SMEs comply with regulations. KryptoGO provides enterprise-level blockchain solutions.
Science VR|The future of learning STEM is experiencing it. ScienceVR host virtual scientists and interactive labs. 區塊鏈的搜尋引擎 KryptoGO

Timeless-economy|Matching People’s Time for Services. Actuating Service Economy by Building a Service Marketplace on Calendar. 時間與服務媒合平台

Dcard|The biggest anonymous social network for young generation in Taiwan. 台灣最大匿名社群網站 Dcard

Melten|Melten is a data-driven solution provider. It facilitates medical institutions to collect patient data via connected devices and bio sensors, including EHR, vitals, behaviors, images, and sounds, with ONE platform. 給中小型電商的數據分析工具

Meet.Jobs| leveraging on social referral and community endorsement, is a headhunting platform focusing on international and professional talents. Meet.Jobs currently has talents, employer users and job opportunities in 17 countries. 獵頭平台 Meet.jobs

MH GoPower| an innovator and manufacturer of high performance Si-based Vertical Multi-Junction PV cells that enable laser power transmission for power over fiber (PoF) and power beaming applications using 9xx nm~1070 nm lasers. （阿雅有看沒有懂，某個厲害的新創）

Glossika|Glossika sorts spoken languages by structure and difficulty, delivering memory, pronunciation and fluency skills to learners between any two languages. 語言學習平台 Glossika

Construct Studio| a San Francisco based VR & AR creative production agency. As an industry leader in immersive interactive content, they have worked with healthcare, airlines, the automotive industry, marketing agencies and Hollywood studios to set the standard for visually stunning and emotionally engaging VR & AR content. 虛擬增廣實境公司 @Construct Studio

另外還有
手機控制的隨身攜帶針灸器 OHA
生物科技領域加速器 Biohub
讓攝影師把作品放到國外圖庫網站變現的平台 Amplframe
基因數據分析工具 Atgenomix
幫醫生細胞分析精準的數據分析工具 五甫科技 Wolf Dataware
籃球球友社群平台與智慧籃球場 PICKUPS
太陽能募資平台 Kiwi Power
個人化大麻 Margen（美國合法州限定）
等等

根據計算，100萬人遊行隊伍要從維多利亞公園排到廣東；200萬人遊行則要排到泰國。

順道一提香港15～30歲人口約莫100出頭萬人。以照片人群幾乎都是此年齡帶來看，兩個數字都是明顯誇大太多了。

另一個可以參考的是1969年的Woodstock Music & Art Fair，幾天內湧進40萬人次，照片看起來也是滿山滿谷的人。（http://sites.psu.edu/…/upl…/sites/851/2013/01/Woodstock3.jpg）

當年40萬人次引發驚人的大塞車，幾乎花十幾個小時才逐漸清場。

而香港遊行清場速度明顯快得多。

順道一提，因此運動而認定「你的父母不愛你」的白痴論述也如同文化大革命時的「爹親娘親不如毛主席親」般開始出現：

https://www.facebook.com/SaluteToHKPolice/videos/350606498983830/UzpfSTUyNzM2NjA3MzoxMDE1NjMyMTM4NjY3MTA3NA/

EVERY MAJOR NEWS outlet in the world is reporting that two million people, well over a quarter of our population, joined a single protest.
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It’s an astonishing thought that filled an enthusiastic old marcher like me with pride. Unfortunately, it’s almost certainly not true.
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A march of two million people would fill a street that was 58 kilometers long, starting at Victoria Park in Hong Kong and ending in Tanglangshan Country Park in Guangdong, according to one standard crowd estimation technique.
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If the two million of us stood in a queue, we’d stretch 914 kilometers (568 miles), from Victoria Park to Thailand. Even if all of us marched in a regiment 25 people abreast, our troop would stretch towards the Chinese border.
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Yes, there was a very large number of us there. But getting key facts wrong helps nobody. Indeed, it could hurt the protesters more than anyone.
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For math geeks only, here’s a discussion of the actual numbers that I hope will interest you whatever your political views.
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DO NUMBERS MATTER?
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People have repeatedly asked me to find out “the real number” of people at the recent mass rallies in Hong Kong.
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I declined for an obvious reason: There was a huge number of us. What does it matter whether it was hundreds of thousands or a million? That’s not important.
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But my critics pointed out that the word “million” is right at the top of almost every report about the marches. Clearly it IS important.
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FIRST, THE SCIENCE
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In the west, drone photography is analyzed to estimate crowd sizes.
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This reporter apologizes for not having found a comprehensive database of drone images of the Hong Kong protests.
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But we can still use related methods, such as density checks, crowd-flow data and impact assessments. Universities which have gathered Hong Kong protest march data using scientific methods include Hong Kong Polytechnic University, Hong Kong University of Science and Technology, University of Hong Kong, and Hong Kong Baptist University.
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DENSITY CHECKS
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Figures gathered in the past by Hong Kong Polytechnic specialists using satellite photo analysis found a density level of one square meter per marcher. Modern analysis suggests this remains roughly accurate.
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I know from experience that Hong Kong marches feature long periods of normal spacing (one square meter or one and half per person, walking) and shorter periods of tight spacing (half a square meter or less per person, mostly standing).
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JOINERS AND SPEED
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We need to include people who join halfway. In the past, a Hong Kong University analysis using visual counting methods cross-referenced with one-on-one interviews indicated that estimates should be boosted by 12% to accurately reflect late joiners. These days, we’re much more generous in estimating joiners.
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As for speed, a Hong Kong Baptist University survey once found a passing rate of 4,000 marchers every ten minutes.
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Videos of the recent rallies indicates that joiner numbers and stop-start progress were highly erratic and difficult to calculate with any degree of certainty.
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DISTANCE MULTIPLIED BY DENSITY
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But scientists have other tools. We know the walking distance between Victoria Park and Tamar Park is 2.9 kilometers. Although there was overspill, the bulk of the marchers went along Hennessy Road in Wan Chai, which is about 25 meters (or 82 feet) wide, and similar connected roads, some wider, some narrower.
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Steve Doig, a specialist in crowd analysis approached by the Columbia Journalism Review (CJR), analyzed an image of Hong Kong marchers to find a density level of 7,000 people in a 210-meter space. Although he emphasizes that crowd estimates are never an exact science, that figure means one million Hong Kong marchers would need a street 18.6 miles long – which is 29 kilometers.
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Extrapolating these figures for the June 16 claim of two million marchers, you’d need a street 58 kilometers long.
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Could this problem be explained away by the turnover rate of Hong Kong marchers, which likely allowed the main (three kilometer) route to be filled more than once?
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The answer is yes, to some extent. But the crowd would have to be moving very fast to refill the space a great many times over in a single afternoon and evening. It wasn’t. While I can walk the distance from Victoria Park to Tamar in 41 minutes on a quiet holiday afternoon, doing the same thing during a march takes many hours.
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More believable: There was a huge number of us, but not a million, and certainly not two million.
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IMPACT MEASUREMENTS
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A second, parallel way of analyzing the size of the crowd is to seek evidence of the effects of the marchers’ absence from their normal roles in society.
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If we extract two million people out of a population of 7.4 million, many basic services would be severely affected while many others would grind to a complete halt.
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Manpower-intensive sectors of society, such as transport, would be badly affected by mass absenteeism. Industries which do their main business on the weekends, such as retail, restaurants, hotels, tourism, coffee shops and so on would be hard hit. Round-the-clock operations such as hospitals and emergency services would be severely troubled, as would under-the-radar jobs such as infrastructure and utility maintenance.
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There seems to be no evidence that any of that happened in Hong Kong.
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HOW DID WE GET INTO THIS MESS?
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To understand that, a bit of historical context is necessary.
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In 2003, a very large number of us walked from Victoria Park to Central. The next day, newspapers gave several estimates of crowd size.
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The differences were small. Academics said it was 350,000 plus. The police counted 466,000. The organizers, a group called the Civil Rights Front, rounded it up to 500,000.
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No controversy there. But there was trouble ahead.
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THINGS FALL APART
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At a repeat march the following year, it was obvious to all of us that our numbers were far lower that the previous year. The people counting agreed: the academics said 194,000 and the police said 200,000.
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But the Civil Rights Front insisted that there were MORE than the previous year’s march: 530,000 people.
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The organizers lost credibility even with us, their own supporters. To this day, we all quote the 2003 figure as the high point of that period, ignoring their 2004 invention.
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THE TRUTH COUNTS
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The organizers had embarrassed the marchers. The following year several organizations decided to serve us better, with detailed, scientific counts.
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After the 2005 march, the academics said the headcount was between 60,000 and 80,000 and the police said 63,000. Separate accounts by other independent groups agreed that it was below 100,000.
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But the organizers? The Civil Rights Front came out with the awkward claim that it was a quarter of a million. Ouch. (This data is easily confirmed from multiple sources in newspaper archives.)
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AN UNEXPECTED TWIST
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But then came a twist. Some in the Western media chose to present ONLY the organizer’s “outlier” claim.
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“Dressed in black and chanting ‘one man, one vote’, a quarter of a million people marched through Hong Kong yesterday,” said the Times of London in 2005.
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“A quarter of a million protesters marched through Hong Kong yesterday to demand full democracy from their rulers in Beijing,” reported the UK Independent.
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It became obvious that international media outlets were committed to emphasizing whichever claim made the Hong Kong government (and by extension, China) look as bad as possible. Accuracy was nowhere in the equation.
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STRATEGICALLY CHOSEN
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At universities in Hong Kong, there were passionate discussions about the apparent decision to pump up the numbers as a strategy, with the international media in mind. Activists saw two likely positive outcomes.
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First, anyone who actually wanted the truth would choose a middle point as the “real” number: thus it was worth making the organizers’ number as high as possible. (The police could be presented as corrupt puppets of Beijing.)
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Second, international reporters always favored the largest number, since it implicitly criticized China. Once the inflated figure was established in the Western media, it would become the generally accepted figure in all publications.
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Both of the activists’ predictions turned out to be bang on target. In the following years, headcounts by social scientists and police were close or even impressively confirmed the other—but were ignored by the agenda-driven international media, who usually printed only the organizers’ claims.
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SKIP THIS SECTION
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Skip this section unless you want additional examples to reinforce the point.
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In 2011, researchers and police said that between 63,000 and 95,000 of us marched. Our delightfully imaginative organizers multiplied by four to claim there were 400,000 of us.
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In 2012, researchers and police produced headcounts similar to the previous year: between 66,000 and 97,000. But the organizers claimed that it was 430,000. (These data can also be easily confirmed in any newspaper archive.)
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SKIP THIS SECTION TOO
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Unless you’re interested in the police angle. Why are police figures seen as lower than others? On reviewing data, two points emerge.
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First, police estimates rise and fall with those of independent researchers, suggesting that they function correctly: they are not invented. Many are slightly lower, but some match closely and others are slightly higher. This suggests that the police simply have a different counting method.
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Second, police sources explain that live estimates of attendance are used for “effective deployment” of staff. The number of police assigned to work on the scene is a direct reflection of the number of marchers counted. Thus officers have strong motivation to avoid deliberately under-estimating numbers.
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RECENT MASS RALLIES
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Now back to the present: this hot, uncomfortable summer.
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Academics put the 2019 June 9 rally at 199,500, and police at 240,000. Some people said the numbers should be raised or even doubled to reflect late joiners or people walking on parallel roads. Taking the most generous view, this gave us total estimates of 400,000 to 480,000.
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But the organizers, God bless them, claimed that 1.03 million marched: this was four times the researchers’ conservative view and more than double the generous view.
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The addition of the “.03m” caused a bit of mirth among social scientists. Even an academic writing in the rabidly pro-activist Hong Kong Free Press struggled to accept it. “Undoubtedly, the anti-amendment group added the extra .03 onto the exact one million figure in order to give their estimate a veneer of accuracy,” wrote Paul Stapleton.
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MIND-BOGGLING ESTIMATE
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But the vast majority of international media and social media printed ONLY the organizers’ eyebrow-raising claim of a million plus—and their version soon fed back into the system and because the “accepted” number. (Some mentioned other estimates in early reports and then dropped them.)
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The same process was repeated for the following Sunday, June 16, when the organizers’ frankly unbelievable claim of “about two million” was taken as gospel in the majority of international media.
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“Two million people in Hong Kong protest China's growing influence,” reported Fox News.
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“A record two million people – over a quarter of the city’s population” joined the protest, said the Guardian this morning.
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“Hong Kong leader apologizes as TWO MILLION take to the streets,” said the Sun newspaper in the UK.
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Friends, colleagues, fellow journalists—what happened to fact-checking? What happened to healthy skepticism? What happened to attempts at balance?
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CONCLUSIONS?
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I offer none. I prefer that you do your own research and draw your own conclusions. This is just a rough overview of the scientific and historical data by a single old-school citizen-journalist working in a university coffee shop.
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I may well have made errors on individual data points, although the overall message, I hope, is clear.
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Hong Kong people like to march.
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We deserve better data.
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We need better journalism. Easily debunked claims like “more than a quarter of the population hit the streets” help nobody.
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International media, your hostile agendas are showing. Raise your game.
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Organizers, stop working against the scientists and start working with them.
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Hong Kong people value truth.
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We’re not stupid. (And we’re not scared of math!)

新刊出版 NEW RELEASE !

Voices of Photography 攝影之聲
Issue 25 : 監控 : 科技資本主義及其不滿
Surveillance: Technocapitalism and Its Discontents

歡迎來到2019，在本世紀將加速前往第二個十年的同時，全球正進入新型態的治理境界，一個炫麗繽紛的數位異化年代。科技資本主義鼓吹的美好網路資訊社會、數位公民幻景，現已整合為順從技術應用與網路社群企業的領導，使人在不斷製造的便利、歡愉與安全的服務口號中上癮，聽任其監控我們的一舉一動，將我們挾帶進難以辨識的、以演算法、審查與評分機制流動控管的漩渦之中，牢牢確保現實世界按照既有的政商權力體系運作。當資料從原本網路科技的副產品，變成如今科技資本主義發展的主要目的，成為「資料（影像）」而非「使用者」的我們，如何建立反支配的能力？

在本期《攝影之聲》中，陳界仁揭示當前科技-政經複合體的「全域式」操控警訊，在人類的自我意識存在危機與新種姓制度降臨之前，尋求從中突圍的思考路徑；義大利藝術家保羅．奇理歐對網路重商主義造成個人資料的濫用加以反擊，藉由遊走在法律邊際的藝術介入，提出積極干預與對抗的社會實踐；作為網路藝術的先鋒，鄭淑麗將在威尼斯雙年展台灣館展出的「3×3×6」，延伸邊沁的環形監獄概念，以3D影像掃描、臉部辨識技術與行動應用程式裝置，駭入「數據全景敞視監控」（data panopticon）的當代牢籠，呈現跨域解放的科幻異托邦地景。同時，我們也邀請影像研究學者黃建宏與新媒體藝術家陶亞倫進行深度對談，論析監控結構、影像科技與人性欲望的糾葛關係。

此外，本期收錄多篇專文：張世倫以蘇育賢錄像作品中脫逃移工的影像所引發的監管議題、以及台灣攝影史上第一次全島大規模拍攝身分證的影像事件等，疏理攝影本身隱含的治理元素；孫松榮則從1980年代初、台灣首位銀行搶犯李師科被監視器拍下的身影，乃至高重黎與陳界仁的錄像藝術，剖析體制的視線規訓；施懿珊的網路社會生態實驗與身分發明，持續進行新一波數位統治術的思辨與未來預示；顧錚藉由冷戰時期東德秘密警察遺留的影像檔案，一探諜報監視技術的早年發展；張瑋探尋敏感反映監控體系的當代藝術，思索科技應用與控制之間的辯證啟示。

「攝影書製作現場」單元進入「編輯」階段，特別訪問日本著名攝影出版社蒼穹舍的創辦人、資深圖片編輯大田通貴，並記錄了大田的影像編輯工作實況。「影像香港」單元則論辨十九世紀初、香港第一位攝影師的攝影史推論解讀。

2019年的歷史意義，是為了進入2020政治權力佈局而存在的一年。賽博空間作為兵家必爭之地，權力引發的控制欲也將啟動網路科技新一波的社會效應。在這個政治人物集體網紅化、並試圖將公民鄉民化的詭譎時刻，你我將在歡樂的聲效氣氛中，準備迎接從未經歷過的處境。

● 購買 Order | http://bit.ly/vop25

Welcome to 2019, a dazzling era of digital alienation as this century accelerates into its second decade and the world enters a new state of governance. The glorious information society and visions of a digital citizenry advocated by technocapitalism have integrated into leaders of technology application and Internet social enterprises. We find ourselves hooked on the constant slogans of convenience, pleasure and security, allowing our every move to be monitored while being dragged into a whirlpool whose flow is controlled by an unrecognizable mechanism of algorithm, review and scoring, thereby ensuring that the real world operates in accordance with established political and business powers. As data transforms itself from a by-product of network technology to become the main purpose behind the development of technological capitalism, how do we build the ability to resist domination as we turn from ‘users’ to ‘data (images)’?

In this issue of Voices of Photography, Chieh-Jen Chen rings the alarm on the pervasive control of the current political economy of science and technology, seeking a path of thought towards a way out before the descent of an existential crisis and a new caste system. Italian artist Paolo Cirio strikes back at the abuse of personal data resulting from Internet mercantilism through social practices of active interference and confrontation, using art forms that teeter on the edge of law. As a pioneer of Internet art, Shu-Lea Cheang will be representing Taiwan at the 58th Venice Biennale with “3×3×6”, an extension of Jeremy Bentham’s concept of panopticon. Hacking into the “data panopticon” of a contemporary prison using 3D image scanning, facial recognition technology and mobile applications, a cross-domain and liberated sci-fi heterotopia opens up. At the same time, we have also invited imagery researcher Chien-Hung Huang and new media artist Ya-Lun Tao for an in-depth discussion to analyzing the complex relationship between surveillance structures, imaging technologies and human desires.

Readers will also find a number of essays in this issue: Shih-Lun Chang reveals the political element hidden in photography as he takes a look at the regulatory issues that were sparked from the image of an escaped migrant worker in Yu-Hsien Su’s video work, and the first large-scale identity card photoshoot in the photography history of Taiwan; Song-Yong Sing analyzes the institutional discipline of vision through the images of Shih-Ke Lee, the first bank robber in Taiwan in the early 1980s, that were caught on a surveillance camera, and the video artworks by Chung-Li Kao and Chieh-Jen Chen; Yi-Shan Shih continues to contemplate and predict a future that is dominated by the new digital wave through her Internet social ecological experiments and identity inventions; Gu Zheng explores the early development of espionage surveillance technology through image files left behind by the East German secret police during the Cold War; Chang Wei ponders the dialectical relationship between technology application and control as she looks at contemporary art that consciously reflects the system of surveillance.

The “Photobook Making: Case Study” series enters the “Editing” phase. We have a special interview with Michitaka Ota, the founder of the renowned Japanese photography publishing house, Sokyu-Sha, who is also an experienced image editor, and follow him in action at image editing work. Meanwhile, the “Image Hong Kong” section discusses the interpretation of the photographic history of Hong Kong’s first photographer in the early 19th century.

2019's significance as a year is because it exists for the political power mapping of 2020. As cyberspace turns into a crucial battleground for strategists, the desire for control that comes with power will also trigger a new wave of social implications brought about by Internet technology. In these volatile times when politicians are becoming Internet sensations and trying to turn citizens into netizens, we will be preparing to face never-before-encountered situations in an atmosphere of joyful theatrics.

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Voices of Photography 攝影之聲
www.vopmagazine.com

? เทคนิคต่าง ๆ ที่ใช้ในคลิป
1. การ pull image จาก docker
2. การแสดง images ที่มีในเครื่อง
3. การ run postgres container
4. การทำ data persistence ด้วย volume เพื่อเก็บข้อมูลของฐานข้อมูลไว้

# script สำคัญที่ใช้ในคลิปนี้
# postgres on docker hub
https://hub.docker.com/_/postgres

# pull docker image
docker pull postgres

# list images
docker images

# run postgres on docker
docker run --name pegasus --rm -e POSTGRES_PASSWORD=banana -d -p 5432:5432 postgres

# list process
docker ps -a

# exec command in container
docker exec -it pegasus psql -U postgres

# connect to postgres from terminal
psql -U postgres -h localhost

# stop process
docker stop pegasus

# persist data (using volume)
docker run --name pegasus --rm -e POSTGRES_PASSWORD=banana -d -p 5432:5432 -v pgdatavolume:/var/lib/postgresql/data postgres

เชิญสมัครเป็นสมาชิกของช่องนี้ได้ที่ ► https://www.youtube.com/subscription_center?add_user=prasertcbs
สอน docker ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGJV7UpJs6NVvsf6qaKja9_
สอน PostgreSQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGi_NqmIu43B-PsxA0wtnyH
สอน MySQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GFmJDsZipFCrY6L-0RrBYLT
สอน Microsoft SQL Server 2012, 2014, 2016, 2017 ► https://www.youtube.com/playlist?list=PLoTScYm9O0GH8gYuxpp-jqu5Blc7KbQVn
สอน SQLite ► https://www.youtube.com/playlist?list=PLoTScYm9O0GHjYJA4pfG38M5BcrWKf5s2
สอน SQL สำหรับ Data Science ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGq8M6HO8xrpkaRhvEBsQhw
การเชื่อมต่อกับฐานข้อมูล (SQL Server, MySQL, SQLite) ด้วย Python ► https://www.youtube.com/playlist?list=PLoTScYm9O0GEdZtHwU3t9k3dBAlxYoq59
การใช้ Excel ในการทำงานร่วมกับกับฐานข้อมูล (SQL Server, MySQL, Access) ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGA2sSqNRSXlw0OYuCfDwYk
#prasertcbs_SQL #prasertcbs #prasertcbs_PostgreSQL #docker

? เทคนิคต่าง ๆ ที่ใช้ในคลิป
1. การ pull image จาก docker
2. การแสดง images ที่มีในเครื่อง
3. การ run mysql container
4. การทำ data persistence ด้วย volume เพื่อเก็บข้อมูลของฐานข้อมูลไว้

# script สำคัญที่ใช้ในคลิปนี้
docker --version

# pull docker image
docker pull mysql

# list images
docker images

# run mysql on docker
docker run --name dolphin --rm -p 3306:3306 -e MYSQL_ROOT_PASSWORD=banana -d mysql

# list processes
docker ps -a

# exec command in container
docker exec -it dolphin mysql -u root -p

# connect to mysql from terminal
* mysql -u root -p -h localhost -P 3306 --protocol=tcp
* mysql -u root -p -P 3306 --protocol=tcp
* mysqlsh root@localhost:3306 --sql

# stop process
docker stop dolphin

# persist data (using volume)
docker run --name dolphin --rm -p 3306:3306 -d -e MYSQL_ROOT_PASSWORD=banana -v mysqlvolume:/var/lib/mysql mysql

เชิญสมัครเป็นสมาชิกของช่องนี้ได้ที่ ► https://www.youtube.com/subscription_center?add_user=prasertcbs
สอน docker ► https://www.youtube.com/watch?v=CFIwQvBY_MM&list=PLoTScYm9O0GGJV7UpJs6NVvsf6qaKja9_
สอน MySQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GFmJDsZipFCrY6L-0RrBYLT
สอน PostgreSQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGi_NqmIu43B-PsxA0wtnyH
สอน Microsoft SQL Server 2012, 2014, 2016, 2017 ► https://www.youtube.com/playlist?list=PLoTScYm9O0GH8gYuxpp-jqu5Blc7KbQVn
สอน SQLite ► https://www.youtube.com/playlist?list=PLoTScYm9O0GHjYJA4pfG38M5BcrWKf5s2
สอน SQL สำหรับ Data Science ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGq8M6HO8xrpkaRhvEBsQhw
การเชื่อมต่อกับฐานข้อมูล (SQL Server, MySQL, SQLite) ด้วย Python ► https://www.youtube.com/playlist?list=PLoTScYm9O0GEdZtHwU3t9k3dBAlxYoq59
การใช้ Excel ในการทำงานร่วมกับกับฐานข้อมูล (SQL Server, MySQL, Access) ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGA2sSqNRSXlw0OYuCfDwYk
#prasertcbs_SQL #prasertcbs #prasertcbs_MySQL #docker

? เทคนิคต่าง ๆ ที่ใช้ในคลิป
1. การ run mssql container พร้อมกำหนด volumne สำหรับ persist data
2. ทดสอบการทำงานของ mssql ผ่าน sqlcmd

# script สำคัญที่ใช้ในคลิปนี้
# check docker version
docker --version

# pull mcr.microsoft.com/mssql/server image
https://hub.docker.com/_/microsoft-mssql-server
docker pull mcr.microsoft.com/mssql/server

# list images
docker image ls

# run a container (แบบไม่มีการ persist data เมื่อมีการลบ container)
docker run --rm --name maroon -e 'ACCEPT_EULA=Y' -e 'MSSQL_SA_PASSWORD=5HEe1Ybq' -p 1433:1433 -d mcr.microsoft.com/mssql/server

# run a container (กำหนดให้ใช้ docker volumne เพื่อ persist data)
docker run --rm --name maroon -e 'ACCEPT_EULA=Y' -e 'MSSQL_SA_PASSWORD=5HEe1Ybq' -p 1433:1433 -v sqlvolume:/var/opt/mssql -d mcr.microsoft.com/mssql/server

# exec sqlcmd client
docker exec -it maroon /opt/mssql-tools/bin/sqlcmd -S localhost -U sa -P 5HEe1Ybq

เชิญสมัครเป็นสมาชิกของช่องนี้ได้ที่ ► https://www.youtube.com/subscription_center?add_user=prasertcbs
สอน docker ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGJV7UpJs6NVvsf6qaKja9_
สอน Microsoft SQL Server 2012, 2014, 2016, 2017 ► https://www.youtube.com/playlist?list=PLoTScYm9O0GH8gYuxpp-jqu5Blc7KbQVn
สอน MySQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GFmJDsZipFCrY6L-0RrBYLT
สอน PostgreSQL ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGi_NqmIu43B-PsxA0wtnyH
สอน SQLite ► https://www.youtube.com/playlist?list=PLoTScYm9O0GHjYJA4pfG38M5BcrWKf5s2
สอน SQL สำหรับ Data Science ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGq8M6HO8xrpkaRhvEBsQhw
การเชื่อมต่อกับฐานข้อมูล (SQL Server, MySQL, SQLite) ด้วย Python ► https://www.youtube.com/playlist?list=PLoTScYm9O0GEdZtHwU3t9k3dBAlxYoq59
การใช้ Excel ในการทำงานร่วมกับกับฐานข้อมูล (SQL Server, MySQL, Access) ► https://www.youtube.com/playlist?list=PLoTScYm9O0GGA2sSqNRSXlw0OYuCfDwYk
#prasertcbs_SQL #prasertcbs #prasertcbs_MySQL #docker