Achieving maintainability with some of Terraform’s more advanced features.
Here, in part 2, our goal is maintainability. We’ll take a data-driven approach. Adding new users will be mere data entry. Along the way, we’ll split our project into multiple files, logically. That’ll make it easier to add more functionality in part…
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#programming #devops #infrastructure #data #software-engineering
파이썬 무료 강의 (활용편6 - 이미지 처리)입니다.
OpenCV 를 이용한 다양한 이미지 처리 기법과 재미있는 프로젝트를 진행합니다.
누구나 볼 수 있도록 쉽고 재미있게 제작하였습니다. ^^
(0:02:18) 2.활용편 6 이미지 처리 소개
(0:08:41) 4.이미지 출력
(0:21:51) 5.동영상 출력 #1 파일
(0:29:58) 6.동영상 출력 #2 카메라
(0:34:23) 7.도형 그리기 #1 빈 스케치북
(0:39:49) 8.도형 그리기 #2 영역 색칠
(0:42:26) 9.도형 그리기 #3 직선
(0:51:23) 10.도형 그리기 #4 원
(0:55:09) 11.도형 그리기 #5 사각형
(0:58:32) 12.도형 그리기 #6 다각형
(1:09:23) 13.텍스트 #1 기본
(1:17:45) 14.텍스트 #2 한글 우회
(1:24:14) 15.파일 저장 #1 이미지
(1:29:27) 16.파일 저장 #2 동영상
(1:39:29) 17.크기 조정
(1:50:16) 18.이미지 자르기
(1:57:03) 19.이미지 대칭
(2:01:46) 20.이미지 회전
(2:06:07) 21.이미지 변형 - 흑백
(2:11:25) 22.이미지 변형 - 흐림
(2:18:03) 23.이미지 변형 - 원근 #1
(2:27:45) 24.이미지 변형 - 원근 #2
[반자동 문서 스캐너 프로젝트]
(2:32:50) 25.미니 프로젝트 1 - #1 마우스 이벤트 등록
(2:42:06) 26.미니 프로젝트 1 - #2 기본 코드 완성
(2:49:54) 27.미니 프로젝트 1 - #3 지점 선 긋기
(2:55:24) 28.미니 프로젝트 1 - #4 실시간 선 긋기
(3:01:52) 29.이미지 변형 - 이진화 #1 Trackbar
(3:14:37) 30.이미지 변형 - 이진화 #2 임계값
(3:20:26) 31.이미지 변형 - 이진화 #3 Adaptive Threshold
(3:28:34) 32.이미지 변형 - 이진화 #4 오츠 알고리즘
(3:32:22) 33.이미지 변환 - 팽창
(3:41:10) 34.이미지 변환 - 침식
(3:45:56) 35.이미지 변환 - 열림 & 닫힘
(3:54:10) 36.이미지 검출 - 경계선
(4:05:08) 37.이미지 검출 - 윤곽선 #1 기본
(4:15:26) 38.이미지 검출 - 윤곽선 #2 찾기 모드
(4:20:46) 39.이미지 검출 - 윤곽선 #3 면적
[카드 검출 & 분류기 프로젝트]
(4:27:42) 40.미니프로젝트 2
(4:41:25) 42.환경설정 및 기본 코드 정리
(4:54:48) 43.눈과 코 인식하여 도형 그리기
(5:10:42) 44.그림판 이미지 씌우기
(5:20:52) 45.캐릭터 이미지 씌우기
(5:40:53) 47.마치며 (학습 참고 자료)
수업에 필요한 이미지, 동영상 자료 링크입니다.
고양이 이미지 : https://pixabay.com/images/id-2083492/
크기 : 640 x 390
파일명 : img.jpg
고양이 동영상 : https://www.pexels.com/video/7515833/
크기 : SD (360 x 640)
파일명 : video.mp4
신문 이미지 : https://pixabay.com/images/id-350376/
크기 : 1280 x 853
파일명 : newspaper.jpg
카드 이미지 1 : https://pixabay.com/images/id-682332/
크기 : 1280 x 1019
파일명 : poker.jpg
책 이미지 : https://www.pexels.com/photo/1029807/
크기 : Small (640 x 853)
파일명 : book.jpg
눈사람 이미지 : https://pixabay.com/images/id-1300089/
크기 : 1280 x 904
파일명 : snowman.png
카드 이미지 2 : https://pixabay.com/images/id-161404/
크기 : 640 x 408
파일명 : card.png
퀴즈용 동영상 : https://www.pexels.com/video/3121459/
크기 : HD (1280 x 720)
파일명 : city.mp4
프로젝트용 동영상 : https://www.pexels.com/video/3256542/
크기 : Full HD (1920 x 1080)
파일명 : face_video.mp4
프로젝트용 캐릭터 이미지 : https://www.freepik.com/free-vector/cute-animal-masks-video-chat-application-effect-filters-set_6380101.htm
파일명 : right_eye.png (100 x 100), left_eye.png (100 x 100), nose.png (300 x 100)
무료 이미지 편집 도구 : https://pixlr.com/kr/
(Pixlr E -Advanced Editor)
If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition
Using data as a part of your marketing plan can have a tremendous impact on your overall results, which is why data-driven marketing has become the standard for many agencies.
However, data-driven marketing may require many businesses to rethink the way they work, especially when it comes to cooperation between their various teams.
You may have heard about the concept of collaboration and automating processes before - something referred to as webops. Now an increasing number of companies are throwing marketing into the mix.
Among the most important factors is a close working relationship between marketing and web development teams if a business wants to make the most of data-driven marketing.
#data-driven #data-driven-marketing #web-development #marketing-data-science #teamwork #data-driven-development #data-driven-decision-making #webops
The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.
This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.
As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).
This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.
#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management
Tableau Software has announced a new study developed in conjunction with YouGov, to explore how organisations in the Asia Pacific and Japan (APJ) have used data during COVID pandemic. The survey noted that data-driven companies in India are more resilient and confident during the pandemic, compared to non-data-driven companies.
According to the data, 83% of data-driven companies in India have reported reaping critical business advantages during the pandemic. Along with that, the survey revealed that 62% of organisations believe that leveraging data can provide multiple and vast benefits to businesses, including more effective communication with stakeholders. Another 58% organisation noted making faster strategic business decisions with 56% witnessing increasing cross-team collaboration. Further, the data stated that 48% of organisations have managed to make their business more agile.
Being data-driven is also allowing organisations to be more optimistic towards this turbulent time. The survey stated that around 76% of organisations are confident and looking forward to a promising future for their business.
While data-driven companies are reaping its benefits, the non-data-driven companies are facing massive challenges in grasping the importance of data. This demonstrates the prevailing disconnect of how businesses leveraging data and the potential for organisations to benefit from a more data-driven approach.
#news #data advantages #data driven companies #data driven decisions india #data driven organisation #data driven organisations gained advantage amid pandemic