subtitle: 진로 설정과 기술스택
데이터 분석가를 희망하는 분들에게 조금이나마 도움이 되고자 만든 발표자료 입니다.
데이터 분석가로 진로를 잡기 이전에 본인의 현재 수준을 직시하고 목표를 명확하게 하셨으면 합니다.
데이터 분석은 첫 진입은 쉬울 수 있으나 그 지식의 넓이와 깊이를 알게되면 평생 공부해야되는 분야임을 느끼실 것입니다.
공부습관이 몸에 베이지 않으면 하루하루 뒤쳐지는 느낌을 받는 곳이라 단단히 마음먹으셔야 합니다.
가장 섹시한 직업일 수 있으나 (한국에서는) 연봉이 그렇게 까지 섹시하진 않습니다.
데이터 분석 강의/자문/외주 문의는 아래 이메일로 부탁드립니다.
contact@rloha.io
< 2016 3rd UX Trend Report Part1>
라이트브레인 UX 트렌드 리포트 UX Discovery는 해외 다양한 매체들을 통해 하루 평균 50여건의 트렌드를 탐색, 수집, 검토하며 UX적 관점에서 분야별로 분석해서 정리됩니다.
2016 UX Discovery 3호에서는 본격적인 AI시대의 진입을 맞아 선보이는 다양한 AI제품들과 서비스 그리고 빅데이터를 활용한 지진감지 경고앱과 같은 최신앱에서 가상현실, 웨어러블 등 뉴 UX 트랜드들도 한번에 살펴 보실 수 있습니다.
이중 1부에서는 새로운 앱(New App), 인공지능(Artificial Intelligence), 가상현실(Virtual Reality), 증강현실(Augmented Reality) 분야의 최신 트렌드를 담고 있으며
전체 리포트는 총 248페이지로, 나머지 내용 및 자세한 정보는 라이트브레인 웹사이트(www.rightbrain.co.kr)와 블로그에서 확인할 수 있습니다.
subtitle: 진로 설정과 기술스택
데이터 분석가를 희망하는 분들에게 조금이나마 도움이 되고자 만든 발표자료 입니다.
데이터 분석가로 진로를 잡기 이전에 본인의 현재 수준을 직시하고 목표를 명확하게 하셨으면 합니다.
데이터 분석은 첫 진입은 쉬울 수 있으나 그 지식의 넓이와 깊이를 알게되면 평생 공부해야되는 분야임을 느끼실 것입니다.
공부습관이 몸에 베이지 않으면 하루하루 뒤쳐지는 느낌을 받는 곳이라 단단히 마음먹으셔야 합니다.
가장 섹시한 직업일 수 있으나 (한국에서는) 연봉이 그렇게 까지 섹시하진 않습니다.
데이터 분석 강의/자문/외주 문의는 아래 이메일로 부탁드립니다.
contact@rloha.io
< 2016 3rd UX Trend Report Part1>
라이트브레인 UX 트렌드 리포트 UX Discovery는 해외 다양한 매체들을 통해 하루 평균 50여건의 트렌드를 탐색, 수집, 검토하며 UX적 관점에서 분야별로 분석해서 정리됩니다.
2016 UX Discovery 3호에서는 본격적인 AI시대의 진입을 맞아 선보이는 다양한 AI제품들과 서비스 그리고 빅데이터를 활용한 지진감지 경고앱과 같은 최신앱에서 가상현실, 웨어러블 등 뉴 UX 트랜드들도 한번에 살펴 보실 수 있습니다.
이중 1부에서는 새로운 앱(New App), 인공지능(Artificial Intelligence), 가상현실(Virtual Reality), 증강현실(Augmented Reality) 분야의 최신 트렌드를 담고 있으며
전체 리포트는 총 248페이지로, 나머지 내용 및 자세한 정보는 라이트브레인 웹사이트(www.rightbrain.co.kr)와 블로그에서 확인할 수 있습니다.
7월 12일 세미나 신청방법 안내
1. ux1@ux1korea.com으로 이름/직장/연락처/이메일을 적어서 신청
2. 신청확인 메일을 받은후, 계좌(국민은행 465101-01-208865. 예금주-조성봉(UX1))로 50,000원을 입금
3. 신청 완료
세미나 장소 : 토즈 강남2호점(위치)
세미나 일시 : 2014년 7월 12일 오후 2시
문의 : 02-3486-4211
Portfolio Optimization Under UncertaintyAdam Butler
This document summarizes a guest lecture on portfolio optimization under uncertainty. The lecture discusses that risk is the probability of not achieving financial objectives. It is explained that investing should minimize this risk. Different portfolio optimization techniques are explored, including equal weighting, naive risk parity, robust risk parity, and mean-variance optimization using different return estimates. Dynamic parameter estimates based on historical volatility and covariance are used to re-optimize portfolios periodically. The results show that thoughtful optimization can materially reduce the probability of not achieving financial objectives compared to traditional static portfolios.
Achieving Asset Optimization: A Strategic Approach To Aligning Assets With Mi...Huron Consulting Group
This document provides an overview of a presentation on achieving asset optimization for healthcare organizations. The presentation aims to help participants strategically align program and facility assets with their mission and market needs. It defines asset optimization and rationalization and outlines a four-step process for planning and executing asset optimization. The steps include understanding the changing market, how current assets meet market needs, identifying gaps, and overcoming obstacles. The presentation also discusses governance imperatives and provides examples of successful and unsuccessful asset optimization efforts.
Driving marketing performance in financial services is subject to unique considerations. Diverse set of distribution channels, complex customer segments, a need to balance branding and promotion, and multiple outcome measures impacting customer value are factors to consider.
This presentation introduces CP Optimizer a model & run optimization engine for solving discrete combinatorial problems with a particular focus on scheduling problems.
Business Analytics and Optimization Introduction (part 2)Raul Chong
Technical introduction to Business Analytics and optimization. This is part 2. Part 1 can be found here: http://www.slideshare.net/rfchong/business-analytics-and-optimization-introduction
The document summarizes an upcoming presentation on branch network optimization for community banks. It provides background on SNL Financial, the company giving the presentation, and outlines the agenda which will discuss the current industry situation, analytical frameworks for optimization, a case study, and critical success factors. Branch growth has moderated in recent years and new technologies are impacting branch transactions, leading many banks to evaluate their branch networks.
How Gartner Helps Across the Entire IT Cost Optimization Life CycleChris Grow
IT Cost Optimization includes the practices, capabilities and behaviors taken by IT organizations and enterprises to balance the constraints of reducing costs, managing service levels and showing the business value of IT in pursuit of enterprise financial imperatives.
AI_introduction and requirements(2024.05.12).pdfLee Chanwoo
AI_introduction and requirements, Considerations for introducing artificial intelligence, understanding machine learning, artificial intelligence security, considerations for introducing ChatGPT, future of generative AI
7월 12일 세미나 신청방법 안내
1. ux1@ux1korea.com으로 이름/직장/연락처/이메일을 적어서 신청
2. 신청확인 메일을 받은후, 계좌(국민은행 465101-01-208865. 예금주-조성봉(UX1))로 50,000원을 입금
3. 신청 완료
세미나 장소 : 토즈 강남2호점(위치)
세미나 일시 : 2014년 7월 12일 오후 2시
문의 : 02-3486-4211
Portfolio Optimization Under UncertaintyAdam Butler
This document summarizes a guest lecture on portfolio optimization under uncertainty. The lecture discusses that risk is the probability of not achieving financial objectives. It is explained that investing should minimize this risk. Different portfolio optimization techniques are explored, including equal weighting, naive risk parity, robust risk parity, and mean-variance optimization using different return estimates. Dynamic parameter estimates based on historical volatility and covariance are used to re-optimize portfolios periodically. The results show that thoughtful optimization can materially reduce the probability of not achieving financial objectives compared to traditional static portfolios.
Achieving Asset Optimization: A Strategic Approach To Aligning Assets With Mi...Huron Consulting Group
This document provides an overview of a presentation on achieving asset optimization for healthcare organizations. The presentation aims to help participants strategically align program and facility assets with their mission and market needs. It defines asset optimization and rationalization and outlines a four-step process for planning and executing asset optimization. The steps include understanding the changing market, how current assets meet market needs, identifying gaps, and overcoming obstacles. The presentation also discusses governance imperatives and provides examples of successful and unsuccessful asset optimization efforts.
Driving marketing performance in financial services is subject to unique considerations. Diverse set of distribution channels, complex customer segments, a need to balance branding and promotion, and multiple outcome measures impacting customer value are factors to consider.
This presentation introduces CP Optimizer a model & run optimization engine for solving discrete combinatorial problems with a particular focus on scheduling problems.
Business Analytics and Optimization Introduction (part 2)Raul Chong
Technical introduction to Business Analytics and optimization. This is part 2. Part 1 can be found here: http://www.slideshare.net/rfchong/business-analytics-and-optimization-introduction
The document summarizes an upcoming presentation on branch network optimization for community banks. It provides background on SNL Financial, the company giving the presentation, and outlines the agenda which will discuss the current industry situation, analytical frameworks for optimization, a case study, and critical success factors. Branch growth has moderated in recent years and new technologies are impacting branch transactions, leading many banks to evaluate their branch networks.
How Gartner Helps Across the Entire IT Cost Optimization Life CycleChris Grow
IT Cost Optimization includes the practices, capabilities and behaviors taken by IT organizations and enterprises to balance the constraints of reducing costs, managing service levels and showing the business value of IT in pursuit of enterprise financial imperatives.
AI_introduction and requirements(2024.05.12).pdfLee Chanwoo
AI_introduction and requirements, Considerations for introducing artificial intelligence, understanding machine learning, artificial intelligence security, considerations for introducing ChatGPT, future of generative AI
100% Serverless big data scale production Deep Learning Systemhoondong kim
- BigData Sale Deep Learning Training System (with GPU Docker PaaS on Azure Batch AI)
- Deep Learning Serving Layer (with Auto Scale Out Mode on Web App for Linux Docker)
- BigDL, Keras, Tensorlfow, Horovod, TensorflowOnAzure
Slides based on "Introduction to Machine Learning with Python" by Andreas Muller and Sarah Guido for Hongdae Machine Learning Study(https://www.meetup.com/Hongdae-Machine-Learning-Study/) (epoch #2)
홍대 머신 러닝 스터디(https://www.meetup.com/Hongdae-Machine-Learning-Study/) (epoch #2)의 "파이썬 라이브러리를 활용한 머신러닝"(옮긴이 박해선) 슬라이드 자료.
Second week, what is an Artivicial Inteligence?.pdfssuser5a82521
Slide 1: Title Slide
Title: "Understanding Artificial Intelligence (AI)"
Subtitle: "An Introduction to the World of Intelligent Machines"
Image: Illustration depicting futuristic technology or AI-related imagery.
Slide 2: Introduction to AI
Definition of AI: "Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and mimic human actions."
Brief history: Highlight key milestones in AI development, from early beginnings to modern advancements.
Slide 3: Types of AI
Narrow AI: Explanation and examples of AI designed for specific tasks, such as virtual assistants, recommendation systems, and self-driving cars.
General AI: Overview of the concept of AGI (Artificial General Intelligence), which aims to mimic human intelligence across a broad range of tasks.
Slide 4: How AI Works
Algorithms: Explanation of how AI systems use algorithms to process data, learn from it, and make decisions or predictions.
Data: Importance of high-quality data for training AI models.
Training: Overview of the training process, including supervised, unsupervised, and reinforcement learning.
Slide 5: Applications of AI
Industry: Examples of AI applications in various industries, such as healthcare (diagnosis assistance), finance (fraud detection), and retail (personalized recommendations).
Everyday life: Highlight how AI impacts daily life, including social media algorithms, virtual assistants, and smart home devices.
Slide 6: Ethical Considerations
Bias: Discussion on the potential for AI systems to inherit biases from their training data and the importance of addressing this issue.
Privacy: Considerations regarding the collection and use of personal data by AI systems, and the need for transparent data practices.
Job displacement: Exploration of the potential impact of AI on employment and the importance of retraining and reskilling the workforce.
Slide 7: Future of AI
Advancements: Speculation on future advancements in AI technology, including the potential for AGI and the ethical implications.
Challenges: Highlighting ongoing challenges in AI research, such as ensuring safety, fairness, and accountability.
Opportunities: Discussion on the potential benefits of AI for society, including improved healthcare, increased productivity, and enhanced decision-making.
Slide 8: Conclusion
Recap: Summarize key points covered in the presentation, emphasizing the significance of AI in today's world.
Call to action: Encourage further exploration of AI-related topics and participation in discussions about its future impact.
Slide 9: Q&A
Open the floor for questions and discussion, allowing the audience to clarify any doubts or share their thoughts on AI.
Slide 10: Thank You
Express appreciation to the audience for their attention and participation in the presentation.
씨마스에서 만든 소프트웨어교육론(저자 정영식, 유정수, 임진숙, 손유경) 책의 파워포인트 자료를 공유합니다.
소프트웨어 교육의 환경, 소프트웨어 교육의 목적, 소프트웨어 교육의 이해, 소프트웨어 교육 과정, 소프트웨어 교수법, 소프트웨어 교재, 소프트웨어 교육의 평가와 분석, 자료, 문제해결과 언플러그드 활동, 알고리즘, 프로그래밍 언어, 융합과학과 소프트웨어, 정보 윤리와 저작권 등으로 구성되어 있습니다.
2018년 7월 5일에 있었던 한국인터넷거버넌스포럼(KrIGF)에서 발표한 "오픈 데이터와 인공지능" 발표자료입니다.
다음과 같은 내용을 담고 있습니다.
* 오픈데이터의 정의
* 오픈데이터의 중요성
* 인공지능
* 인공지능에서 데이터의 중요성
* 제한된 데이터 환경에서의 문제점
* 인공지능을 위한 오픈데이터의 중요성
* 더 나은 인공지능 시대를 위한 제언
This document discusses automatic evolutionary music composition using genetic algorithms. It introduces algorithmic composition and evolutionary music composition. Various genetic representations and operators for melody are presented, including representing notes as values and using crossover and mutation. Fitness evaluation is discussed, noting it can consider multiple objectives like stability and tension. An interactive system is described that gets user input on fitness. Finally, examples of experiments evolving 4 and 16 bar melodies under a multi-objective genetic algorithm are shown.
Parkinsmism involved in basal ganglia circuitJong MIn Yu
This document discusses Parkinsonism and the basal ganglia circuit approach. It begins with an introduction that defines Parkinsonism as a neurological syndrome characterized by tremors, hypokinesia, rigidity, and postural instability. It affects both motor and non-motor functions and generally impacts older populations. The pathology section explains that the cause is unclear but involves the progressive loss of dopamine-producing brain cells in the substantia nigra, which reduces dopamine in the basal ganglia. The approach to basal ganglia circuit aspect section looks at the normal basal ganglia circuitry and how it is impacted in Parkinson's disease.
The document describes the major blood vessels that supply the brain. The common carotid arteries and vertebro-basilar arteries provide oxygenated blood to the head and neck. These vessels form a circle known as the Circle of Willis at the base of the brain, which allows for collateral blood flow if one portion of the circle is blocked. The main arteries that branch off from the circle include the anterior cerebral artery, middle cerebral artery, and posterior cerebral artery, each supplying different regions of the brain. The lenticulostriate arteries are also described as smaller deep penetrating vessels.
This document discusses declarative memory, which includes both episodic and semantic memory. It defines declarative memory as factual knowledge and memories of past events that are encoded by the hippocampus, entorhinal cortex, and perirhinal cortex. Episodic memory refers to autobiographical memories of specific events and experiences, while semantic memory involves general factual knowledge. The document also discusses the HM case of a patient with amnesia following removal of parts of the hippocampus, and how this case contributed to understanding the brain regions involved in memory formation.
2. Research Topic
• Online algorithm process optimal solution
• In computer science, an online algorithm is one that can process its input
piece-by-piece in a serial fashion, i.e., in the order that the input is fed to
the algorithm, without having the entire input available from the start. In
contrast, an offline algorithm is given the whole problem data from the
beginning and is required to output an answer which solves the problem
at hand. (For example, selection sort requires that the entire list be given
before it can sort it, while insertion sort doesn't.)
• Artificial intelligence
• 인공지능(人工知能)은 철학적으로 인간이나 지성을 갖춘 존재, 혹은 시
스템에 의해 만들어진 지능, 즉 인공적인 지능을 뜻한다. 일반적으로 범
용 컴퓨터에 적용한다고 가정한다. 이 용어는 또한 그와 같은 지능을 만
들 수 있는 방법론이나 실현 가능성 등을 연구하는 과학 분야를 지칭하
기도 한다.
3. Research purposes - Optimization
• 인공지능 프로세스에서 최적화, 처리 효율이 증가되도록 변형
• 실제 알고리즘상에서 적용하여 알고리즘의 수리적 이해를 증진시킴.
• 수리적 모델 설계 이후 구현을 목표로 함.
4. 사용자 : 문자메시지를 읽어줘
시리 : 산토니 리버스에게 문자가 왔습니다. “오늘 파티에 가니?”
사용자 : 답장 보내, “그래 거기서 보자.” 집에 도착하면 선물 챙기는 거 잊지 않게 알려줘.
시리 : 알람에 등록했습니다.
7. AI Communication .
지속적인 데이터 수집과 의사소통 관련 텍스트 분석을 통한 인공지능의 대응 능력 향상
대용량 데이터(Big data) 의 수집 및 유지 비용
+
의사소통 관련 텍스트 분석에 드는 분석 비용.
얼마인지 나도 잘 모름…. 근데 많이 비싸겠지…..
9. Development Environment
• Server : CPU Q6600 (memory : 6GB)
• CORE : 4core(2core : 2node)
• HDD : 1.5TB
• OS : Fedora 17 (64x)
• IDE : Eclipse, Netbean
• Language : JAVA, Python 2.6.*
• IP : 168.188.129.***
10. 관련 연구
• 기계학습 [ Machine Learning ]
• 지능과 밀접히 관계된 것이 학습이다. 사실상, 지능은 배우는 능력 없이는 존재할 수가 없는데
왜냐하면 학습의 주요한 장점은 새로운 지식을 습득하는 수단이기 때문이다. 학습은 장점을 여
러 가지 상황과 사건에 적용하고 사용하게 한다. 그러므로 배우는 능력은 강력한 도구이다.
• Neuro-linguistic programming
• Neuro-linguistic programming (NLP) is an approach
to communication,personal development, and psychotherapy created in the
1970s. The title refers to a stated connection between the neurological
processes ("neuro"), language ("linguistic"), and behavioral patterns that have
been learned through experience ("programming") and can be organized to
achieve specific goals in life.[1][2]According to certain
neuroscientists,[3] psychologists,[4][5] and linguists,[6][7]NLP is unsupported by
current scientific evidence, and uses incorrect and misleading terms and
concepts.
11. Schedule
• - 9, 10 월 :
• 논문 테마 관련 자료 수집
• 관련 연구 기사 및 관련 논문 리뷰
• 주제 선정, 기반 application 구현
• 알고리즘 리뷰 및 개선 논의
• - 10월 :
• 기반 Application 구현
• 알고리즘 최적화 설계 & 가설 수립
• Unit Test & Alpha Test & 가설 검증
• - 11월 :
• Unit Test & Alpha Test & 가설 검증
12. Now – 기반 application 구현
• 개발 환경 세팅
• 서버 준비
• 기반 프로그램 기획
• Application frame 설계
• TCP/IP 기반 채팅프로그램 구현
• Unit test
• AI Process 구현
• Ai algorithm 설계 및 구현(12.10~12.11)
• Unit test
• Application 에 algorithm 적용
• Application test 및 algorithm 적용
• Algorithm 성능 및 개선 검증
• 응용 개발 – 선택 개발
• Moblie application converting - android