Machine learning uses generic models trained on data to make predictions. This document outlines a machine learning course which includes lectures on topics like linear regression and neural networks. Students will complete three mandatory projects and an individual oral exam to assess their understanding of the taught theory and ability to implement machine learning techniques.
El Limonar. 8 magníficas viviendas unifamiliares en parcelas de 400 m² junto al campo de golf proyectado en esa misma zona.
El Limonar. 8 magnificent single family homes on 400 m² parcels next to the golf course planned for the area.
El Limonar. 8 magníficas viviendas unifamiliares en parcelas de 400 m² junto al campo de golf proyectado en esa misma zona.
El Limonar. 8 magnificent single family homes on 400 m² parcels next to the golf course planned for the area.
Brief introduction to web platform knowledge sharing using OSS software, namely WordPress and Public Knowledge Project\'s (PKP) open journal system. Presented at the Oklahoma Library Association meeting on April 23, 2008 in Tulsa, OK.
Readiness To Change, Predictor to Treatment Outcomegugugaga
This is a presentation for class assignment. I did Part 1 of the presentation in Keynote, while i copy and paste my team\'s part (they did in PPT).
I am saying that, Willingness and Motivation to change is a better treatment predictor for Patients..
Filip Panjevic is a Co-Founder and CTO at ydrive.ai - startup dealing with self-driving cars, and one of the founders of Petnica Machine Learning School.
Filip's talk will focus on the story of Petnica School, how did it start, what has changed since the beginning, how the concept of school looks right now and why is that concept good for making new data scientists. This talk will be perfect for people who consider starting their careers in the data science field!
ACL 2018에 다녀오신 NAVER 개발자 분들께서 그 내용을 공유해 주십니다.
1. Overview - Lucy Park
2. Tutorials - Xiaodong Gu
3. Main conference
a. Semantic parsing - Soonmin Bae
b. Dialogue - Kyungduk Kim
c. Machine translation - Zae Myung Kim
d. Summarization - Hye-Jin Min
4. Workshops - Minjoon Seo
Brief introduction to web platform knowledge sharing using OSS software, namely WordPress and Public Knowledge Project\'s (PKP) open journal system. Presented at the Oklahoma Library Association meeting on April 23, 2008 in Tulsa, OK.
Readiness To Change, Predictor to Treatment Outcomegugugaga
This is a presentation for class assignment. I did Part 1 of the presentation in Keynote, while i copy and paste my team\'s part (they did in PPT).
I am saying that, Willingness and Motivation to change is a better treatment predictor for Patients..
Filip Panjevic is a Co-Founder and CTO at ydrive.ai - startup dealing with self-driving cars, and one of the founders of Petnica Machine Learning School.
Filip's talk will focus on the story of Petnica School, how did it start, what has changed since the beginning, how the concept of school looks right now and why is that concept good for making new data scientists. This talk will be perfect for people who consider starting their careers in the data science field!
ACL 2018에 다녀오신 NAVER 개발자 분들께서 그 내용을 공유해 주십니다.
1. Overview - Lucy Park
2. Tutorials - Xiaodong Gu
3. Main conference
a. Semantic parsing - Soonmin Bae
b. Dialogue - Kyungduk Kim
c. Machine translation - Zae Myung Kim
d. Summarization - Hye-Jin Min
4. Workshops - Minjoon Seo
An Online Spark Pipeline: Semi-Supervised Learning and Automatic Retraining w...Databricks
Real-time/online machine learning is an integral piece in the machine learning landscape, particularly in regard to unsupervised learning. Areas such as focused advertising, stock price prediction, recommendation engines, network evolution and IoT streams in smart cities and smart homes are increasing in demand and scale. Continuously-updating models with efficient update methodologies, accurate labeling, feature extraction, and modularity for mixed models are integral to maintaining scalability, precision, and accuracy in high demand scenarios.
This session explores a real-time/online learning algorithm and implementation using Spark Streaming in a hybrid batch/ semi-supervised setting. It presents an easy-to-use, highly scalable architecture with advanced customization and performance optimization. Within this framework, we will examine some of the key methodologies for implementing the algorithm, including partitioning and aggregation schemes, feature extraction, model evaluation and correction over time, and our approaches to minimizing loss and improving convergence. The result is a simple, accurate pipeline that can be easily adapted and scaled to a variety of use cases.
The performance of the algorithm will be evaluated comparatively against existing implementations in both linear and logistic prediction. The session will also cover real-time uses cases of the streaming pipeline using real time-series data and present strategies for optimization and implementation to improve both accuracy and efficiency in a semi-supervised setting.
Introduction to the Non-Technical Project Seminar at the Otto von Guericke Un...Mathias Magdowski
This presentation gives a brief introduction to a seminar about
- scientific working and writing,
- literature survey and reference management,
- proper visualization and
- effective presentations
called "Non-Technical Project Seminar" and offered at the Faculty of Electrical Engineering and Information Technology at the Otto von Guericke University in Magdeburg.
Corresponding E-learning course in Moodle:
https://elearning.ovgu.de/course/view.php?id=808
Law firms & lawyers - rid the manual review of text documents, correspondence, etc. Text Analytics of unstructured documents signals potential knowledge that brings relevance & helps win cases. Moreover, use of text analytics helps offer small firms the same advantage that big firms have. As the information can be used to strengthen solutions and provide advice to attorneys, courtrooms will also benefit from more informed, better prepared legal teams and swift action, keeping long years of litigation away!
Machine learning: A Walk Through School ExamsRamsha Ijaz
When it comes to studying, Machines and Students have one thing in common: Examinations. To perform well on their final evaluations, humans require taking classes, reading books and solving practice quizzes. Similarly, machines need artificial intelligence to memorize data, infer feature correlations, and pass validation standards in order to solve almost any problem. In this quick introductory session, we'll walk through these analogies to learn the core concepts behind Machine Learning, and why it works so well!
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topics and algorithms of which I am aware. The depth of CO!Irer•liM
topic or method is exactly right and appropriate. Each a/grorirtmti �r�
in pseudocode that is s , icient for any interested readers to
working implementation in a computer language of their choice.
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Discussion on distributed, parallel, and incremental algorithms is outst:tlftfi!tr··· '��
-Z an Obradovic, Temple Univef'Sf1tv
Margaret Dunham offers the experienced data base professional or graduate
level Computer Science student an introduction to the full spectrum of Data
Mining concepts and algorithms. Using a database perspective throughout,
Professor Dunham examines algorithms, data structures, data types, and
complexity of algorithms and space. This text emphasizes the use of data
mining concepts in real-world applications with large database components.
KEY FEATURES:
.. Covers advanced topics such as Web Mining and Spatialrremporal mining
Includes succinct coverage of Data Warehousing, OLAP, Multidimensional
Data, and Preprocessing
Provides case studies
Offers clearly written algorithms to better understand techniques
Includes a reference on how to use Prototypes and DM products
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
3. Machine Learning: what is it? We have data We want 0 1 2 3 4 5 6 7 8 9 ...a model ...a prediction
4. Machine Learning: what is it? We have data We want 0 1 2 3 4 5 6 7 8 9 ...a model ...a prediction In machine learning we use generic models that we train from the data.
5. Machine Learning: what is it? We have data We want 0 1 2 3 4 5 6 7 8 9 ...a model ...a prediction In machine learning we use generic models that we train from the data. Prediction is achieved using the trained models .
7. Lectures Mondays: 12 :15-14:00, Shannon 159 Fridays: 12:15-13:00, Shannon 159 When and where http://www.daimi.au.dk/~cstorm/courses/ML_f08/schedule.html Weekly schedule
8.
9. Mandatory Projects Linear Regression Late April Hidden Markov Models Early May Neural Networks Late May There will be three mandatory projects Work in groups of 2-3 students ...implementation, training, experimenting...
11. Exam Individual oral exam (20 min; no preparation) 4-6 questions based on theory from lectures Presentation of mandatory projects and related theory More info later...
12. Schedule Week 1 Crash course in probability theory and statistics Week 2 Linear regression and classification Week 3 Hidden Markov models Week 4 Hidden Markov models (cont.) Week 5 Neural Networks Week 6 Neural Networks (cont.) Week 7 Bits'n'pieces Evaluation of course and information about exam
13. Schedule Week 1 Crash course in probability theory and statistics Week 2 Linear regression and classification Week 3 Hidden Markov models Week 4 Hidden Markov models (cont.) Week 5 Neural Networks Week 6 Neural Networks (cont.) Week 7 Bits'n'pieces Evaluation of course and information about exam
