Constraint Programming - An Alternative Approach to Heuristics in SchedulingEray Cakici
The document summarizes a seminar presentation on using constraint programming (CP) as an alternative approach to heuristics for scheduling problems. It provides an overview of CP, how it works through constraint propagation and backtracking, and how scheduling problems can be modeled in CP. It then presents computational studies comparing CP to mixed integer programming (MIP) and heuristics on semiconductor wafer scheduling problems, flexible job shop scheduling with batching, and parallel batching machines with job release times, weights and sizes. The studies found that CP was able to find optimal solutions faster than MIP formulations and outperformed heuristics on many problem instances.
Sales and Operations Planning (S&OP) at CIMSA Eray Cakici
This document discusses the Sales and Operations Planning (S&OP) project at ÇimSA, a leading white cement producer. It provides an overview of the project, including ÇimSA's supply chain challenges, IBM's solution approach, and achievements. The solution involved building an optimization model integrated with ÇimSA's SAP system to generate optimized production, inventory, transportation, and sales plans. Challenges in deploying optimization projects included ensuring data quality, defining project scope, building trust in the solutions, and dealing with changing business conditions over time.
Multiclass classification using Massively Threaded Multiprocessorssergherrero
This document presents a method for parallelizing multiclass support vector machine (SVM) classification on massively threaded multiprocessors like graphics processing units (GPUs). It begins with background on data growth, multiclass classification, SVMs, related work, and GPU architecture. It then introduces Parallel-Parallel SMO (P2SMO), which parallelizes the sequential minimal optimization (SMO) algorithm used to train SVMs by assigning each thread to optimize two Lagrange multipliers. Performance results demonstrating reduced training and classification time on GPUs are also discussed.
This document provides a summary of David Wood's work experience including roles, technologies, and skills. It lists over 30 roles he has held from 1994 to 2017 across several countries involving technologies like IBM i, RPG, SQL, and various ERP systems. Recent roles in 2017 included verifying exam questions, tutoring, and application support. From 2011-2014 he was IT Leader for Cummins Inc. coordinating projects across multiple locations.
A service to easily connect IBM Planning Analytics (PA) and Watson Studio (WS) / Watson Machine Learning (WML), so that you can easily set up the integration of a deployed Decision Optimization (DO) or Machine Learning (ML) model to be executed from PA.
Tsvi Lev. Practical Explainability for AI - with examplesLviv Startup Club
This document discusses explainable artificial intelligence (XAI) and the need for XAI in applied AI contexts. It notes that applied AI has different requirements than academic research, including the need for stability, compliance, explainability and accountability. Various use cases are discussed that have these requirements, such as medical diagnostics. The document also discusses challenges like bias and concept drift that can occur without XAI. It reviews different approaches to achieving explainability, such as causality analysis and model improvement techniques. Overall, the document advocates for the importance of XAI in ensuring trust and accountability in applied, real-world AI systems.
Real Exams offers IBM 000-061 certification exam with complete detail. Our IBM 000-061 is real study questions and 000-061 training tools updated & complete for IT professionals.
Constraint Programming - An Alternative Approach to Heuristics in SchedulingEray Cakici
The document summarizes a seminar presentation on using constraint programming (CP) as an alternative approach to heuristics for scheduling problems. It provides an overview of CP, how it works through constraint propagation and backtracking, and how scheduling problems can be modeled in CP. It then presents computational studies comparing CP to mixed integer programming (MIP) and heuristics on semiconductor wafer scheduling problems, flexible job shop scheduling with batching, and parallel batching machines with job release times, weights and sizes. The studies found that CP was able to find optimal solutions faster than MIP formulations and outperformed heuristics on many problem instances.
Sales and Operations Planning (S&OP) at CIMSA Eray Cakici
This document discusses the Sales and Operations Planning (S&OP) project at ÇimSA, a leading white cement producer. It provides an overview of the project, including ÇimSA's supply chain challenges, IBM's solution approach, and achievements. The solution involved building an optimization model integrated with ÇimSA's SAP system to generate optimized production, inventory, transportation, and sales plans. Challenges in deploying optimization projects included ensuring data quality, defining project scope, building trust in the solutions, and dealing with changing business conditions over time.
Multiclass classification using Massively Threaded Multiprocessorssergherrero
This document presents a method for parallelizing multiclass support vector machine (SVM) classification on massively threaded multiprocessors like graphics processing units (GPUs). It begins with background on data growth, multiclass classification, SVMs, related work, and GPU architecture. It then introduces Parallel-Parallel SMO (P2SMO), which parallelizes the sequential minimal optimization (SMO) algorithm used to train SVMs by assigning each thread to optimize two Lagrange multipliers. Performance results demonstrating reduced training and classification time on GPUs are also discussed.
This document provides a summary of David Wood's work experience including roles, technologies, and skills. It lists over 30 roles he has held from 1994 to 2017 across several countries involving technologies like IBM i, RPG, SQL, and various ERP systems. Recent roles in 2017 included verifying exam questions, tutoring, and application support. From 2011-2014 he was IT Leader for Cummins Inc. coordinating projects across multiple locations.
A service to easily connect IBM Planning Analytics (PA) and Watson Studio (WS) / Watson Machine Learning (WML), so that you can easily set up the integration of a deployed Decision Optimization (DO) or Machine Learning (ML) model to be executed from PA.
Tsvi Lev. Practical Explainability for AI - with examplesLviv Startup Club
This document discusses explainable artificial intelligence (XAI) and the need for XAI in applied AI contexts. It notes that applied AI has different requirements than academic research, including the need for stability, compliance, explainability and accountability. Various use cases are discussed that have these requirements, such as medical diagnostics. The document also discusses challenges like bias and concept drift that can occur without XAI. It reviews different approaches to achieving explainability, such as causality analysis and model improvement techniques. Overall, the document advocates for the importance of XAI in ensuring trust and accountability in applied, real-world AI systems.
Real Exams offers IBM 000-061 certification exam with complete detail. Our IBM 000-061 is real study questions and 000-061 training tools updated & complete for IT professionals.
A (Not So Short) Introduction to CP Optimizer for SchedulingPhilippe Laborie
This document provides an introduction to a tutorial on CP Optimizer for scheduling. It discusses CP Optimizer's modeling concepts for scheduling problems that are based on intervals of time, sequences of intervals, and functions of time. These concepts provide a more natural way to model scheduling problems compared to traditional mathematical programming and constraint programming approaches. The document gives examples of how piecewise-linear functions, stepwise functions, and transition matrices can be used as constant structures in CP Optimizer models. It also introduces the concept of interval variables, which represent intervals of time, and optional interval variables, which allow intervals to be present or absent in solutions.
- The document discusses IBM's approach to deploying and delivering case management solutions to customers. It describes IBM's focus on providing comprehensive solutions, not just products, to address customer needs.
- The solution workshop is summarized as a 3-5 day collaborative session between IBM and the customer to design an initial case management solution mockup and understand how IBM Case Manager can address business challenges.
- An overview of IBM's prescriptive case management journey is provided, outlining stages from an initial pilot project to enterprise-wide adoption and the goals and maturity challenges at each stage.
Decision Optimization - CPLEX Optimization Studio - Product Overview(2).PPTXSanjayKPrasad2
This document provides an overview of IBM's prescriptive analytics software IBM ILOG CPLEX Optimization Studio (COS). It discusses how prescriptive analytics fits within the analytics portfolio including descriptive, predictive, and prescriptive analytics. It then describes COS's target audiences, key features like optimization engines and modeling tools, example applications that have achieved significant cost savings, and how optimization models are created and deployed.
The document describes an online railway reservation project developed on a mainframe environment using COBOL programming language. The front-end was designed using CICS and the backend database was maintained using DB2. The project automated the ticket generation process for passengers allowing them to view, book and cancel tickets online. The document also includes the professional experience, skills and qualifications of the job applicant.
The document discusses software project planning and estimation. It covers topics like why planning is important, project planning purpose and context, estimating resources, and software estimation methods like COCOMO. COCOMO models like basic, intermediate and detailed COCOMO are explained. The document also provides an example of using the basic COCOMO model to estimate effort and development time for a project of size 400k LOC across organic, semidetached and embedded modes.
The document provides details about Rexx Shih's profile, including his work experience, skills, education, certifications, and project experience. It consists of several sections:
- Personal profile and skills: Outlines Rexx's expertise in IT solutions, project management certifications, and business analysis skills.
- Work experience: Lists Rexx's roles and responsibilities in various companies from 2007-2014, including as a system engineer, business analyst, and section manager.
- Education: Details Rexx's master's degree in information technology management.
- Project experience: Provides summaries of 9 projects Rexx worked on, describing objectives, roles, technologies used, and benefits achieved. Projects involved areas like project
Pankaj Sarkar has over 15 years of experience in content management systems including Adobe CQ/AEM, OpenText, and Jahia. He has extensive experience designing, developing, and implementing a variety of applications on these platforms. Currently he works as a Manager of Technology at SapientNitro, where he leads projects involving CMS solutions and provides expertise in Adobe AEM.
The document discusses developing recommendation reports for technical problems and projects. It provides examples of recommendation reports that:
1) Describe the nature of a technical problem involving clock skew in high-frequency digital systems. It recommends developing a SAR-controlled DLL deskew circuit to address the problem.
2) Describe an issue with constructing 3D faces from 2D images. It recommends developing an efficient 3D face model that can generate a 3D image from three 2D photos, reducing time and improving precision over manual methods.
1. Om Prakash Gupta has over 12 years of experience in telecom BSS/OSS systems including interconnect billing, roaming, rating, invoicing and mediation systems. He has worked with products such as Ericsson SDP, CSG Interconnect, Kenan FX, and Comverse One.
2. He has experience as a solution architect and project manager for Airtel India's national mobile number portability project and Airtel Africa's IT transformation project involving roaming, mediation and content partner revenue settlement systems across 17 African countries.
3. He has also worked as a business analyst on Mobistar's billing transformation project to migrate to the Comverse One billing product and
Sridhar_SAP_ABAP_TechnicalConsultant_ResumeSridhar V
Sridhar has over 11 years of experience in SAP with expertise in ABAP, XI, FI, SD, and MM modules. He has worked on projects involving requirements gathering, design, development, testing, and implementation. Sridhar has extensive experience developing reports, interfaces, conversions, forms and other objects to meet business needs across various industries. He is highly skilled in ABAP programming and integrating SAP solutions.
This document defines the deliverables for a project to improve the computer delivery time process. Deliverable 2 involves defining the project boundaries, which includes writing a problem statement identifying the defect as computers being delivered in 11 days on average versus the 10 day goal, drafting a project charter with details of the scope, timeline and benefits, and setting a goal of decreasing the delivery time to 9 days by a target date. It provides guidance on tools to use for each deliverable such as a SIPOC, inclusion/exclusion list, and elevator speech.
Srinivasan Chinnappa has over 17 years of experience in mainframe technologies such as COBOL, DB2, CICS, JCL, and various mainframe tools. He has worked across multiple industries including banking, insurance, manufacturing, retail, and telecom. Some of his responsibilities have included analyzing requirements, preparing designs, developing and maintaining mainframe applications, and working on migration projects.
This document contains details about Sasikumar Selvaraj including his contact information, work experience, technical skills, and education. He has over 7 years of experience working as a Software Engineering Senior Analyst for Accenture on various projects for clients like Travelers Insurance and First Data Corp. His technical expertise includes mainframe platforms, Z/OS, Cobol, VSAM, DB2, and various Microsoft office and development tools. He has a Master of Science degree from Pondicherry University and a Bachelor of Science from the same university.
Tips and hints for an effective cosmic learning process gained from industria...IWSM Mensura
This document provides an overview of common issues encountered in COSMIC functional size measurement (FSM) trainings conducted with industrial professionals. It describes the diverse audience profiles and objectives of the trainings. The trainings involve both group theory sessions and individual practical exercises using company case studies. Some highlighted issues include difficulties understanding why FSM is a good estimation method, focusing on technical rather than requirements aspects, accounting for non-functional requirements, determining the appropriate level of granularity, and properly identifying data groups and data movement. The document aims to better understand challenges faced by trainees and improve the training approach.
This document is a resume for Guru Prasad H G summarizing his career experience and qualifications. He has over 7 years of experience in software testing for various projects in the telecom and retail industries. His experience includes testing billing systems, preparing test plans and reports, and working on projects for clients like IKEA, T-Mobile UK, Kraft, and British Telecom. He is currently working as a consultant for Capgemini and has experience in both manual and automation testing methods.
Optimization: from mathematical tools to real applicationsPhilippe Laborie
This document discusses the gap between mathematical optimization tools and real-world applications. It covers several key areas in bridging this gap, including having different stakeholders with different objectives, using appropriate language and terminology, properly defining the problem, dealing with data issues, determining good solutions, and facilitating solution display and user interaction. The goal is to provide approximate answers to the right real-world problems, rather than perfectly solving simplified mathematical abstractions.
This document provides a summary of Arindom Kumar Biswas's professional experience and qualifications. It summarizes that he has over 7 years of experience working as a Project Lead and Technical Lead on Mainframe projects for insurance companies like Cognizant Technology Solutions and MetLife. It also lists his technical skills which include languages like COBOL, JCL, and databases like VSAM, DB2. Finally, it provides details of some of the projects he has worked on, including conversions from legacy to new platforms and product launches.
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
A (Not So Short) Introduction to CP Optimizer for SchedulingPhilippe Laborie
This document provides an introduction to a tutorial on CP Optimizer for scheduling. It discusses CP Optimizer's modeling concepts for scheduling problems that are based on intervals of time, sequences of intervals, and functions of time. These concepts provide a more natural way to model scheduling problems compared to traditional mathematical programming and constraint programming approaches. The document gives examples of how piecewise-linear functions, stepwise functions, and transition matrices can be used as constant structures in CP Optimizer models. It also introduces the concept of interval variables, which represent intervals of time, and optional interval variables, which allow intervals to be present or absent in solutions.
- The document discusses IBM's approach to deploying and delivering case management solutions to customers. It describes IBM's focus on providing comprehensive solutions, not just products, to address customer needs.
- The solution workshop is summarized as a 3-5 day collaborative session between IBM and the customer to design an initial case management solution mockup and understand how IBM Case Manager can address business challenges.
- An overview of IBM's prescriptive case management journey is provided, outlining stages from an initial pilot project to enterprise-wide adoption and the goals and maturity challenges at each stage.
Decision Optimization - CPLEX Optimization Studio - Product Overview(2).PPTXSanjayKPrasad2
This document provides an overview of IBM's prescriptive analytics software IBM ILOG CPLEX Optimization Studio (COS). It discusses how prescriptive analytics fits within the analytics portfolio including descriptive, predictive, and prescriptive analytics. It then describes COS's target audiences, key features like optimization engines and modeling tools, example applications that have achieved significant cost savings, and how optimization models are created and deployed.
The document describes an online railway reservation project developed on a mainframe environment using COBOL programming language. The front-end was designed using CICS and the backend database was maintained using DB2. The project automated the ticket generation process for passengers allowing them to view, book and cancel tickets online. The document also includes the professional experience, skills and qualifications of the job applicant.
The document discusses software project planning and estimation. It covers topics like why planning is important, project planning purpose and context, estimating resources, and software estimation methods like COCOMO. COCOMO models like basic, intermediate and detailed COCOMO are explained. The document also provides an example of using the basic COCOMO model to estimate effort and development time for a project of size 400k LOC across organic, semidetached and embedded modes.
The document provides details about Rexx Shih's profile, including his work experience, skills, education, certifications, and project experience. It consists of several sections:
- Personal profile and skills: Outlines Rexx's expertise in IT solutions, project management certifications, and business analysis skills.
- Work experience: Lists Rexx's roles and responsibilities in various companies from 2007-2014, including as a system engineer, business analyst, and section manager.
- Education: Details Rexx's master's degree in information technology management.
- Project experience: Provides summaries of 9 projects Rexx worked on, describing objectives, roles, technologies used, and benefits achieved. Projects involved areas like project
Pankaj Sarkar has over 15 years of experience in content management systems including Adobe CQ/AEM, OpenText, and Jahia. He has extensive experience designing, developing, and implementing a variety of applications on these platforms. Currently he works as a Manager of Technology at SapientNitro, where he leads projects involving CMS solutions and provides expertise in Adobe AEM.
The document discusses developing recommendation reports for technical problems and projects. It provides examples of recommendation reports that:
1) Describe the nature of a technical problem involving clock skew in high-frequency digital systems. It recommends developing a SAR-controlled DLL deskew circuit to address the problem.
2) Describe an issue with constructing 3D faces from 2D images. It recommends developing an efficient 3D face model that can generate a 3D image from three 2D photos, reducing time and improving precision over manual methods.
1. Om Prakash Gupta has over 12 years of experience in telecom BSS/OSS systems including interconnect billing, roaming, rating, invoicing and mediation systems. He has worked with products such as Ericsson SDP, CSG Interconnect, Kenan FX, and Comverse One.
2. He has experience as a solution architect and project manager for Airtel India's national mobile number portability project and Airtel Africa's IT transformation project involving roaming, mediation and content partner revenue settlement systems across 17 African countries.
3. He has also worked as a business analyst on Mobistar's billing transformation project to migrate to the Comverse One billing product and
Sridhar_SAP_ABAP_TechnicalConsultant_ResumeSridhar V
Sridhar has over 11 years of experience in SAP with expertise in ABAP, XI, FI, SD, and MM modules. He has worked on projects involving requirements gathering, design, development, testing, and implementation. Sridhar has extensive experience developing reports, interfaces, conversions, forms and other objects to meet business needs across various industries. He is highly skilled in ABAP programming and integrating SAP solutions.
This document defines the deliverables for a project to improve the computer delivery time process. Deliverable 2 involves defining the project boundaries, which includes writing a problem statement identifying the defect as computers being delivered in 11 days on average versus the 10 day goal, drafting a project charter with details of the scope, timeline and benefits, and setting a goal of decreasing the delivery time to 9 days by a target date. It provides guidance on tools to use for each deliverable such as a SIPOC, inclusion/exclusion list, and elevator speech.
Srinivasan Chinnappa has over 17 years of experience in mainframe technologies such as COBOL, DB2, CICS, JCL, and various mainframe tools. He has worked across multiple industries including banking, insurance, manufacturing, retail, and telecom. Some of his responsibilities have included analyzing requirements, preparing designs, developing and maintaining mainframe applications, and working on migration projects.
This document contains details about Sasikumar Selvaraj including his contact information, work experience, technical skills, and education. He has over 7 years of experience working as a Software Engineering Senior Analyst for Accenture on various projects for clients like Travelers Insurance and First Data Corp. His technical expertise includes mainframe platforms, Z/OS, Cobol, VSAM, DB2, and various Microsoft office and development tools. He has a Master of Science degree from Pondicherry University and a Bachelor of Science from the same university.
Tips and hints for an effective cosmic learning process gained from industria...IWSM Mensura
This document provides an overview of common issues encountered in COSMIC functional size measurement (FSM) trainings conducted with industrial professionals. It describes the diverse audience profiles and objectives of the trainings. The trainings involve both group theory sessions and individual practical exercises using company case studies. Some highlighted issues include difficulties understanding why FSM is a good estimation method, focusing on technical rather than requirements aspects, accounting for non-functional requirements, determining the appropriate level of granularity, and properly identifying data groups and data movement. The document aims to better understand challenges faced by trainees and improve the training approach.
This document is a resume for Guru Prasad H G summarizing his career experience and qualifications. He has over 7 years of experience in software testing for various projects in the telecom and retail industries. His experience includes testing billing systems, preparing test plans and reports, and working on projects for clients like IKEA, T-Mobile UK, Kraft, and British Telecom. He is currently working as a consultant for Capgemini and has experience in both manual and automation testing methods.
Optimization: from mathematical tools to real applicationsPhilippe Laborie
This document discusses the gap between mathematical optimization tools and real-world applications. It covers several key areas in bridging this gap, including having different stakeholders with different objectives, using appropriate language and terminology, properly defining the problem, dealing with data issues, determining good solutions, and facilitating solution display and user interaction. The goal is to provide approximate answers to the right real-world problems, rather than perfectly solving simplified mathematical abstractions.
This document provides a summary of Arindom Kumar Biswas's professional experience and qualifications. It summarizes that he has over 7 years of experience working as a Project Lead and Technical Lead on Mainframe projects for insurance companies like Cognizant Technology Solutions and MetLife. It also lists his technical skills which include languages like COBOL, JCL, and databases like VSAM, DB2. Finally, it provides details of some of the projects he has worked on, including conversions from legacy to new platforms and product launches.
Similar to Navy Training Scheduling - Euro 2021 (20)
Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You...Aggregage
This webinar will explore cutting-edge, less familiar but powerful experimentation methodologies which address well-known limitations of standard A/B Testing. Designed for data and product leaders, this session aims to inspire the embrace of innovative approaches and provide insights into the frontiers of experimentation!
State of Artificial intelligence Report 2023kuntobimo2016
Artificial intelligence (AI) is a multidisciplinary field of science and engineering whose goal is to create intelligent machines.
We believe that AI will be a force multiplier on technological progress in our increasingly digital, data-driven world. This is because everything around us today, ranging from culture to consumer products, is a product of intelligence.
The State of AI Report is now in its sixth year. Consider this report as a compilation of the most interesting things we’ve seen with a goal of triggering an informed conversation about the state of AI and its implication for the future.
We consider the following key dimensions in our report:
Research: Technology breakthroughs and their capabilities.
Industry: Areas of commercial application for AI and its business impact.
Politics: Regulation of AI, its economic implications and the evolving geopolitics of AI.
Safety: Identifying and mitigating catastrophic risks that highly-capable future AI systems could pose to us.
Predictions: What we believe will happen in the next 12 months and a 2022 performance review to keep us honest.
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake
The Ipsos - AI - Monitor 2024 Report.pdfSocial Samosa
According to Ipsos AI Monitor's 2024 report, 65% Indians said that products and services using AI have profoundly changed their daily life in the past 3-5 years.
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
4th Modern Marketing Reckoner by MMA Global India & Group M: 60+ experts on W...Social Samosa
The Modern Marketing Reckoner (MMR) is a comprehensive resource packed with POVs from 60+ industry leaders on how AI is transforming the 4 key pillars of marketing – product, place, price and promotions.
Codeless Generative AI Pipelines
(GenAI with Milvus)
https://ml.dssconf.pl/user.html#!/lecture/DSSML24-041a/rate
Discover the potential of real-time streaming in the context of GenAI as we delve into the intricacies of Apache NiFi and its capabilities. Learn how this tool can significantly simplify the data engineering workflow for GenAI applications, allowing you to focus on the creative aspects rather than the technical complexities. I will guide you through practical examples and use cases, showing the impact of automation on prompt building. From data ingestion to transformation and delivery, witness how Apache NiFi streamlines the entire pipeline, ensuring a smooth and hassle-free experience.
Timothy Spann
https://www.youtube.com/@FLaNK-Stack
https://medium.com/@tspann
https://www.datainmotion.dev/
milvus, unstructured data, vector database, zilliz, cloud, vectors, python, deep learning, generative ai, genai, nifi, kafka, flink, streaming, iot, edge
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
3. BS, Industrial Engineering, Baskent University
MS, PhD, Industrial Engineering, University of Arkansas
15 + years of industry experience
(Transplace, Zero Gap Analytics, IBM)
Adjunct Faculty at Bogazici, Koc, Baskent Universities
Author and Referee of many academic articles
Introduction
3
7. 7
USE CASE
Optimize business-
critical operations
scheduling to meet
demand, under
multiple operational
restrictions and
business rules.
IBM Data Science & AI Elite and
Capita Consulting work together
to effectively solve challenging
Resource-Constrained
Scheduling Optimization
Problems
CASE STUDY
EXPECTED BENEFIT
Deliver optimized
recommendations.
Boost computational time
and problem scale with
IBM CPLEX.
Measure and control the
business impact of the
scheduling.
UNIQUE CHALLENGE
Many resource conflicts
induced by availability and
capacity of resources,
jobs’ release date and
demand due date.
Multiple objectives.
Various use-case
scenarios to be targeted.
LOGO
“Working with the team
and using CPLEX we were
able to reduce the time to
find a feasible solution for
this highly complex
problem from hours to
seconds.”
Vince Powell
Partner, Solutions Lead