Deep Learning for Computer Vision: Welcome (UPC TelecomBCN 2016)
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http://imatge-upc.github.io/telecombcn-2016-dlcv/ Deep learning technologies are at the core of the current revolution in artificial intelligence for multimedia data analysis. The convergence of big annotated data and affordable GPU hardware has allowed the training of neural networks for data analysis tasks which had been addressed until now with hand-crafted features. Architectures such as convolutional neural networks, recurrent neural networks and Q-nets for reinforcement learning have shaped a brand new scenario in signal processing. This course will cover the basic principles and applications of deep learning to computer vision problems, such as image classification, object detection or text captioning.
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![Day 1 Lecture 1
Welcome
[course site]](https://image.slidesharecdn.com/dlcvd1l1welcome-160715092622/85/Deep-Learning-for-Computer-Vision-Welcome-UPC-TelecomBCN-2016-1-320.jpg)
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Conditional Random Fields - Vidya Venkiteswaran
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International trends in learning analytics was presented by Dr. Doug Clow of the Open University UK. The Open University has over 200,000 students, 5,000 tutors, and 1,000 academic staff. It analyzes over 1 billion views and 3 million transactions per day. Learning analytics is defined as measuring, collecting, analyzing, and reporting data about learners and contexts to understand and optimize learning. International activities in learning analytics include conferences, workshops, and publications. Trends from the 2014 Learning Analytics Summer Institute included a focus on privacy, ethics, readiness, technology, research issues, and new contexts like MOOCs.
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#ALTNWESIG 2016 - University of Manchester Wednesday 9th November 2016
This is our final event of 2016 and we are bound for the University of Manchester on Wednesday 9th November from 1pm to 4pm (Lunch will be provided)
The finalised programme will follow but is likely to include these topics:
BYOD/Mobile Strategy
Teaching Excellence Framework (TEF) white paper
Turnitin Feedback Studio
VLE Review
Digital Capabilities
Time for networking
If you have any issues, case studies or other topics relevant to the group then get involved! Please contact Alex livasp@liverpool.ac.uk or Chris c.r.jones1@ljmu.ac.uk
Get in touch with Diane Bennett Diane.Bennett@manchester.ac.uk if you have any dietary requirements
The North West England Sig (#ALTNWESIG) exists to provide a network for the exchange of ideas and practices in relation to current issues in educational technology with the aim of supporting the informed use of learning technologies in North West England. Join us in our Google Plus Community
Hashtag for the day will be #ALTNWESIG
Look forward to seeing you all soon
Alex, Chris & Diane
Student experience experts group meet up, April 2020
This document summarizes the agenda for the 46th meeting of Jisc's student experience experts group. The meeting will include presentations and discussions on the future of assessment, transforming assessment and feedback through technology, and equipping staff with digital capabilities. Presentations will cover Jisc's research on the future of assessment, examples of effective practice from Manchester Metropolitan University and Preston's College, and supporting new students' digital experience. The agenda also includes virtual coffee breaks and a lunch break. Recordings and materials from the event will be made available on Jisc's website.
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This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
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HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Columbus Data & Analytics Wednesdays - June 2024
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System Design Case Study: Building a Scalable E-Commerce Platform - Hiike
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AWS Cloud Cost Optimization Presentation.pptx
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5th LF Energy Power Grid Model Meet-up Slides
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Best 20 SEO Techniques To Improve Website Visibility In SERP
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
Taking AI to the Next Level in Manufacturing.pdf
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
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Deep Learning for Computer Vision: Welcome (UPC TelecomBCN 2016)
- 1. Day 1 Lecture 1 Welcome [course site]
- 2. 2 Instructors Xavier Giro-i-Nieto • Web: https://imatge.upc.edu/web/people/xavier-giro Associate Professor at Universitat Politecnica de Catalunya (UPC)
- 3. 3 Elisa Sayrol Instructors Associate Professor at Universitat Politècnica de Catalunya (UPC) Web: https://imatge.upc.edu/web/people/elisa-sayrol
- 4. 4 Amaia Salvador PhD Candidate Image Processing Group (GPI), Universitat Politècnica de Catalunya https://imatge.upc.edu/web/people/amaia-salvador Escola d’Enginyeria de Terrassa UPC - ESEIAAT Instructors
- 5. 5 Jordi Torres 5 • Web: http://www.JordiTorres/Barcelona • Twitter: @JordiTorresBCN Professor at Universitat Politècnica de Catalunya (UPC) Instructors
- 6. 6 Eva Mohedano Instructors PhD Candidate Insight Centre for Data Analytics https://www.insight-centre.org/users/eva-mohedano
- 7. 7 Kevin McGuinness Research Fellow at Dublin City University (DCU) Insight Centre for Data Analytics https://www.insight-centre.org/users/kevin-mcguinness Instructors
- 8. 8 Management Instructor Area Xavier Giró Coordination Kevin McGuinness Lectures Elisa Sayrol Logistics & Evaluation Jordi Torres Lab Amaia Salvador Project Eva Mohedano Web and online material
- 9. 9 Teaching assistants / contributors
- 13. 13
- 14. 14 Motivation Source: 25 Best jobs in America (Glassdoor) The best job in the world: Data scientist.
- 15. 15 The Economist, “Million-dollar babies” (02/04/2016) Motivation
- 16. 16 Nature, “AI talent grab sparks excitement and concern” (26/04/2016) Motivation
- 17. 17 Motivation Exponential increase of generated multimedia content..
- 18. 18 Motivation ...keeping a record of the memorable personal moments... Pope Francis @ Philippines, 2015 (Source: AP Photo/Bullit Marquez)
- 19. 19 Motivation Pope Francis @ Ecuador, 2015 (Source: AP) ...keeping a record of the memorable personal moments...
- 20. 20 Motivation …(or not). Pope Francis @ USA, 2015
- 21. 21 Motivation This data growth is motivated by ubiquous mobile access to...
- 22. 22 Motivation ...the Internet (for visual data transmission)... Source: Cisco Visual Networking Index (VNI)
- 23. 23 Motivation ...and people ! Person of the Year (2006)
- 24. 24 Motivation Need computer vision tools to extract knowledge from these large amount of rich visual data.
- 25. 25 Course sites https://piazza.com/class#summer2016/230360 http://telecombcn.deeplearning.barcelona
- 26. 26 Schedule: Project & Tensorflow BSc Students without project Project Teams 1 & 2 Project Teams 3, 4, 5 3-4 Lectures 4-5 TensorFlow Project 5-6 Lectures 6-7 Project (optional) Project Tensorflow Monday to Thursday Friday BSc Students without project Project Teams 1 & 2 Project Teams 3, 4, 5 3-4 Project expo Teams 3, 4 & 5 4-5 TensorFlow Closing 5-6 Project expo Teams 1 & 2 6-7 Closing Tensorflow
- 27. 27 Grading BSc MSc Online Tests 60% 30% Lab 30% 30% Project - 30% Communication - 10% Attendance 10% -10% x miss day
- 28. 28 Grading: Online tests [Online test preview]