This document discusses building intelligent solutions with graphs using Neo4j services. It provides an overview of Neo4j's professional services which include training, solution delivery, and packaged services. It also discusses adding AI/ML to solutions, real-world examples, and best practices. Typical technical requirements and the process of delivering solutions from use cases are described. Benefits of Neo4j solutions include acceleration, increased maturity, and shorter implementation cycles.
How to Build a ML Platform Efficiently Using Open-SourceDatabricks
Fast-growing startups usually face a common set of challenges when employing machine learning. Data scientists are expected to work on new products and develop new models as well as iterate on existing ones. Once in production, models should be continuously monitored and regularly maintained as the infrastructure evolves. Before too long, data scientists end up spending most of their time doing maintenance and firefighting of existing models instead of creating new ones.
At GetYourGuide, we faced these challenges and decided to think about machine learning development holistically, which led us to our machine learning platform. Our platform uses MLflow to keep track of our machine learning life-cycle and ease the development experience. To integrate our models into our production environment, we also need to deal with additional requirements like API specification, SLOs and monitoring. To empower our data scientists, we have built a templating system that takes care of the heavy lifting of going to production, leveraging software engineering tools and ML-specific ones like BentoML.
In this talk we will present:
– Our previous approaches for deploying models and their tradeoffs
– Our data science and platform principles
– The main functionalities of our platform
– A live demo to create a new service
– Our learnings in the process
Drive Away Fraudsters With Driverless AI - Venkatesh Ramanathan, Senior Data ...Sri Ambati
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/r9S3xchrzlY.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://twitter.com/h2oai.
- - -
Abstract:
Venkatesh will explore how driverless AI is helping to keep fraudsters at bay. Share results from experiments conducted on large scale payment transaction data.
Venkatesh's Bio:
Venkatesh is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection. He has over 20+ years experience in designing, developing and leading teams to build scalable server-side software. In addition to being an expert in big-data technologies, Venkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP) and had worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.
Not only, is our data is getting not just more complex but also more connected. In order not to lose sight of the web of information, but to use it as a source of new insights and opportunities, technologies such as graph databases can help.
For both analytical and transactional use cases, they allow efficient storage, retrieval, and processing of networked data without loss of detail. In this talk, we want to get to know existing tools and techniques for graph data processing.
How to Build a ML Platform Efficiently Using Open-SourceDatabricks
Fast-growing startups usually face a common set of challenges when employing machine learning. Data scientists are expected to work on new products and develop new models as well as iterate on existing ones. Once in production, models should be continuously monitored and regularly maintained as the infrastructure evolves. Before too long, data scientists end up spending most of their time doing maintenance and firefighting of existing models instead of creating new ones.
At GetYourGuide, we faced these challenges and decided to think about machine learning development holistically, which led us to our machine learning platform. Our platform uses MLflow to keep track of our machine learning life-cycle and ease the development experience. To integrate our models into our production environment, we also need to deal with additional requirements like API specification, SLOs and monitoring. To empower our data scientists, we have built a templating system that takes care of the heavy lifting of going to production, leveraging software engineering tools and ML-specific ones like BentoML.
In this talk we will present:
– Our previous approaches for deploying models and their tradeoffs
– Our data science and platform principles
– The main functionalities of our platform
– A live demo to create a new service
– Our learnings in the process
Drive Away Fraudsters With Driverless AI - Venkatesh Ramanathan, Senior Data ...Sri Ambati
Presented at #H2OWorld 2017 in Mountain View, CA.
Enjoy the video: https://youtu.be/r9S3xchrzlY.
Learn more about H2O.ai: https://www.h2o.ai/.
Follow @h2oai: https://twitter.com/h2oai.
- - -
Abstract:
Venkatesh will explore how driverless AI is helping to keep fraudsters at bay. Share results from experiments conducted on large scale payment transaction data.
Venkatesh's Bio:
Venkatesh is a senior data scientist at PayPal where he is working on building state-of-the-art tools for payment fraud detection. He has over 20+ years experience in designing, developing and leading teams to build scalable server-side software. In addition to being an expert in big-data technologies, Venkatesh holds a Ph.D. degree in Computer Science with specialization in Machine Learning and Natural Language Processing (NLP) and had worked on various problems in the areas of Anti-Spam, Phishing Detection, and Face Recognition.
Not only, is our data is getting not just more complex but also more connected. In order not to lose sight of the web of information, but to use it as a source of new insights and opportunities, technologies such as graph databases can help.
For both analytical and transactional use cases, they allow efficient storage, retrieval, and processing of networked data without loss of detail. In this talk, we want to get to know existing tools and techniques for graph data processing.
The New Normal – Delivering Remote Professional ServicesNeo4j
The new normal for IT professionals is working out of home offices. While Neo4j Pre-Sales and Professional Services have always provided remote services, we have recently fine-tuned our remote delivery of workshops, trainings, bootcamps, health checks, expert services and more. We have boosted functionality, with extra conferencing tools, VPN and data security features, while offering more flexible schedules and timelines.
In this webinar, Stefan Kolmar will present some of the Neo4j services packages and demonstrate examples of successful implementation and deployment of Neo4j based projects. The webinar will focus on adapting Neo4j services to the needs of today's world, maintaining productivity by enabling virtual teams to implement and deliver projects remotely.
Blackboard Learn Deployment: A Detailed Update of Managed Hosting and SaaS De...Blackboard APAC
Blackboard has deployed cloud solutions for well over a decade and is very excited to launch our new SaaS offering at the Teaching and Learning conference. The session will explore Blackboard’s continued commitment to managed hosting, partnership with IBM/AWS and next generation SaaS offerings that offer institutions unique control over their innovation journey.
Gateway Group - Corporate Presentation - Corporate Presentation, IT Company Corporate Presentation, Software Development Company Presentation - May 2013
These slides were presentet at Munich Meetup of April 18th. They present the reco4j project, its high view and it vision.
See the project site for more details here: http://www.reco4j.org
This presentation shows reco4j features and vision. In particular we add the new concept of context aware recommendation and how we integrate it into reco4j. In this new presentation there is also some piece of code that show how simple is integrate our software. See the project site for more details here: http://www.reco4j.org
TLC2018 Thomas Haver: Transform with Enterprise AutomationAnna Royzman
Thomas Haver explains how to build a robust automation solution across the Enterprise to improve application quality, testing efficiency, and lower operational costs. He shows how to leverage all current resources to achieve this goal without affecting project delivery time at Test Leadership Congress 2018.
http://testleadershipcongress-ny.com
Marvin é um ambicioso projeto de código aberto que se concentra em ajudar equipes a entregar soluções de machine learning de maneira ágil. A plataforma oferece uma arquitetura padronizada e agnóstica de linguagem, de alta escala e baixa latência enquanto simplifica o processo de exploração e modelagem de projetos de IA.
[DSC DACH 23] Go with the flow – Track your machine learning lifecycle using ...DataScienceConferenc1
Based on the prediction of house prices, this tutorial covers the reasons and the advantages of versioning machine learning models using the open-source platform MLflow. This platform allows to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. Participants will gain insights into the initial setup, the tracking of ML experiments and the final registration of a production ready model.
Github: https://github.com/pdanninger/dsc_dach.git
Neo4j GraphTalks Oslo - Graph Your Business - Rik Van Bruggen, Neo4jNeo4j
The Neo4j graph database is the fastest growing database engine in the market and has hundreds of customer references across Europe and globally, solving significant technology problems for large Enterprises in Finance, Telco, Retail, Utilities, Logistics and Internet sectors. Typical use cases are Recommendations, Fraud Detection, MDM, Network and Software Analysis and Optimization, Identity and Access Management.
Dutch Oracle Architects Platform - Reviewing Oracle OpenWorld 2017 and New Tr...Lucas Jellema
Not since the rise of Service Oriented Architecture (and the supporting Fusion Middleware technology) over a decade ago have we seen so much rapid change in terms of application and infrastructure architecture. Cloud, Microservices and DevOps are perhaps the most explicit examples – but many other developments in technology, architecture and even the industry at large have an impact on how enterprises consider and employ IT – such as machine learning, IoT, blockchain.
In this session for (infrastructure, solution, application, enterprise, security, data) architects – we will present the main stories, roadmaps and technologies from Oracle OpenWorld 2017 (and JavaOne) that influence, shape and enable architecture. We will brainstorm together on the consequences of the new directions outlined by Oracle – and coming our way from other quarters. We are seeing a a lot of change. New opportunities arise – that may become challenges or threats if we fail to recognize and embrace the change in time. This session will help us all to get a better handle on the winds in enterprise IT in general and in Oracle land in particular.
Among the topics we will present and discuss are:
- The Only Way is Up – the inevitable and imminent move from on premises to the cloud, and upwards in the stack – from IaaS to SaaS
- Security and Ops in a hybrid landscape (multiple clouds & on premises, multiple technologies & interaction channels)
- Autonomous Database – what, when, how
- Oracle’s cloud strategy, High PaaS and Low PaaS, Open [source] technology (star of the show: Apache Kafka) and the commodization of the traditional Oracle platform
- Container and Cloud Native at Oracle Cloud (Docker, Kubernetes Container Platform, Wercker, Istio Service Mesh, CNCF)
- Serverless
- Java Reborn – for microservices and cloud, modularized (highlights from the JavaOne conference)
- Disruptive: Blockchain, IoT, Machine Learning
Developing and deploying AI solutions on the cloud using Team Data Science Pr...Debraj GuhaThakurta
Presented at: Global Big AI Conference, Santa Clara, Jan 2018 Developing and deploying AI solutions on the cloud using Team Data Science Process (TDSP) and Azure Machine Learning (AML)
Similar to GraphTalk Wien - Intelligente Lösungen mit Graphen erstellen (20)
SOPRA STERIA - GraphRAG : repousser les limitations du RAG via l’utilisation ...Neo4j
Romain CAMPOURCY – Architecte Solution, Sopra Steria
Patrick MEYER – Architecte IA Groupe, Sopra Steria
La Génération de Récupération Augmentée (RAG) permet la réponse à des questions d’utilisateur sur un domaine métier à l’aide de grands modèles de langage. Cette technique fonctionne correctement lorsque la documentation est simple mais trouve des limitations dès que les sources sont complexes. Au travers d’un projet que nous avons réalisé, nous vous présenterons l’approche GraphRAG, une nouvelle approche qui utilise une base Neo4j générée pour améliorer la compréhension des documents et la synthèse d’informations. Cette méthode surpasse l’approche RAG en fournissant des réponses plus holistiques et précises.
ADEO - Knowledge Graph pour le e-commerce, entre challenges et opportunités ...Neo4j
Charles Gouwy, Business Product Leader, Adeo Services (Groupe Leroy Merlin)
Alors que leur Knowledge Graph est déjà intégré sur l’ensemble des expériences d’achat de leur plateforme e-commerce depuis plus de 3 ans, nous verrons quelles sont les nouvelles opportunités et challenges qui s’ouvrent encore à eux grâce à leur utilisation d’une base de donnée de graphes et l’émergence de l’IA.
GraphSummit Paris - The art of the possible with Graph TechnologyNeo4j
Sudhir Hasbe, Chief Product Officer, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
GraphAware - Transforming policing with graph-based intelligence analysisNeo4j
Petr Matuska, Sales & Sales Engineering Lead, GraphAware
Western Australia Police Force’s adoption of Neo4j and the GraphAware Hume graph analytics platform marks a significant advancement in data-driven policing. Facing the challenges of growing volumes of valuable data scattered in disconnected silos, the organisation successfully implemented Neo4j database and Hume, consolidating data from various sources into a dynamic knowledge graph. The result was a connected view of intelligence, making it easier for analysts to solve crime faster. The partnership between Neo4j and GraphAware in this project demonstrates the transformative impact of graph technology on law enforcement’s ability to leverage growing volumes of valuable data to prevent crime and protect communities.
GraphSummit Stockholm - Neo4j - Knowledge Graphs and Product UpdatesNeo4j
David Pond, Lead Product Manager, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Shirley Bacso, Data Architect, Ingka Digital
“Linked Metadata by Design” represents the integration of the outcomes from human collaboration, starting from the design phase of data product development. This knowledge is captured in the Data Knowledge Graph. It not only enables data products to be robust and compliant but also well-understood and effectively utilized.
Your enemies use GenAI too - staying ahead of fraud with Neo4jNeo4j
Delivered by Michael Down at Gartner Data & Analytics Summit London 2024 - Your enemies use GenAI too: Staying ahead of fraud with Neo4j.
Fraudsters exploit the latest technologies like generative AI to stay undetected. Static applications can’t adapt quickly enough. Learn why you should build flexible fraud detection apps on Neo4j’s native graph database combined with advanced data science algorithms. Uncover complex fraud patterns in real-time and shut down schemes before they cause damage.
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxNeo4j
Delivered by Sreenath Gopalakrishna, Director of Software Engineering at BT, and Dr Jim Webber, Chief Scientist at Neo4j, at Gartner Data & Analytics Summit London 2024 this presentation examines how knowledge graphs and GenAI combine in real-world solutions.
BT Group has used the Neo4j Graph Database to enable impressive digital transformation programs over the last 6 years. By re-imagining their operational support systems to adopt self-serve and data lead principles they have substantially reduced the number of applications and complexity of their operations. The result has been a substantial reduction in risk and costs while improving time to value, innovation, and process automation. Future innovation plans include the exploration of uses of EKG + Generative AI.
Workshop: Enabling GenAI Breakthroughs with Knowledge Graphs - GraphSummit MilanNeo4j
Look beyond the hype and unlock practical techniques to responsibly activate intelligence across your organization’s data with GenAI. Explore how to use knowledge graphs to increase accuracy, transparency, and explainability within generative AI systems. You’ll depart with hands-on experience combining relationships and LLMs for increased domain-specific context and enhanced reasoning.
Workshop 1. Architecting Innovative Graph Applications
Join this hands-on workshop for beginners led by Neo4j experts guiding you to systematically uncover contextual intelligence. Using a real-life dataset we will build step-by-step a graph solution; from building the graph data model to running queries and data visualization. The approach will be applicable across multiple use cases and industries.
LARUS - Galileo.XAI e Gen-AI: la nuova prospettiva di LARUS per il futuro del...Neo4j
Roberto Sannino, Larus Business Automation
Nel panorama sempre più complesso dei progetti basati su grafi, LARUS ha consolidato una solida esperienza pluriennale, costruendo un rapporto di fiducia e collaborazione con Neo4j. Attraverso il LARUS Labs, ha sviluppato componenti e connettori che arricchiscono l’ecosistema Neo4j, contribuendo alla sua continua evoluzione. Tutto questo know-how è stato incanalato nell’innovativa soluzione Galileo.XAI di LARUS, un prodotto all’avanguardia che, integrato con la Generative AI, offre una nuova prospettiva nel mondo dell’Intelligenza Artificiale Spiegabile applicata ai grafi. In questo speech, si esplorerà il percorso di crescita di LARUS in questo settore, mettendo in luce le potenzialità della soluzione Galileo.XAI nel guidare l’innovazione e la trasformazione digitale.
GraphSummit Milan - Visione e roadmap del prodotto Neo4jNeo4j
van Zoratti, VP of Product Management, Neo4j
Scoprite le ultime innovazioni di Neo4j che consentono un’intelligenza guidata dalle relazioni su scala. Scoprite le più recenti integrazioni nel cloud e i miglioramenti del prodotto che rendono Neo4j una scelta essenziale per gli sviluppatori che realizzano applicazioni con dati interconnessi e IA generativa.
GraphSummit Milan & Stockholm - Neo4j: The Art of the Possible with GraphNeo4j
Dr Jesús Barrasa, Head of Solutions Architecture for EMEA, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Your Digital Assistant.
Making complex approach simple. Straightforward process saves time. No more waiting to connect with people that matter to you. Safety first is not a cliché - Securely protect information in cloud storage to prevent any third party from accessing data.
Would you rather make your visitors feel burdened by making them wait? Or choose VizMan for a stress-free experience? VizMan is an automated visitor management system that works for any industries not limited to factories, societies, government institutes, and warehouses. A new age contactless way of logging information of visitors, employees, packages, and vehicles. VizMan is a digital logbook so it deters unnecessary use of paper or space since there is no requirement of bundles of registers that is left to collect dust in a corner of a room. Visitor’s essential details, helps in scheduling meetings for visitors and employees, and assists in supervising the attendance of the employees. With VizMan, visitors don’t need to wait for hours in long queues. VizMan handles visitors with the value they deserve because we know time is important to you.
Feasible Features
One Subscription, Four Modules – Admin, Employee, Receptionist, and Gatekeeper ensures confidentiality and prevents data from being manipulated
User Friendly – can be easily used on Android, iOS, and Web Interface
Multiple Accessibility – Log in through any device from any place at any time
One app for all industries – a Visitor Management System that works for any organisation.
Stress-free Sign-up
Visitor is registered and checked-in by the Receptionist
Host gets a notification, where they opt to Approve the meeting
Host notifies the Receptionist of the end of the meeting
Visitor is checked-out by the Receptionist
Host enters notes and remarks of the meeting
Customizable Components
Scheduling Meetings – Host can invite visitors for meetings and also approve, reject and reschedule meetings
Single/Bulk invites – Invitations can be sent individually to a visitor or collectively to many visitors
VIP Visitors – Additional security of data for VIP visitors to avoid misuse of information
Courier Management – Keeps a check on deliveries like commodities being delivered in and out of establishments
Alerts & Notifications – Get notified on SMS, email, and application
Parking Management – Manage availability of parking space
Individual log-in – Every user has their own log-in id
Visitor/Meeting Analytics – Evaluate notes and remarks of the meeting stored in the system
Visitor Management System is a secure and user friendly database manager that records, filters, tracks the visitors to your organization.
"Secure Your Premises with VizMan (VMS) – Get It Now"
Quarkus Hidden and Forbidden ExtensionsMax Andersen
Quarkus has a vast extension ecosystem and is known for its subsonic and subatomic feature set. Some of these features are not as well known, and some extensions are less talked about, but that does not make them less interesting - quite the opposite.
Come join this talk to see some tips and tricks for using Quarkus and some of the lesser known features, extensions and development techniques.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Listen to the keynote address and hear about the latest developments from Rachana Ananthakrishnan and Ian Foster who review the updates to the Globus Platform and Service, and the relevance of Globus to the scientific community as an automation platform to accelerate scientific discovery.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Strategies for Successful Data Migration Tools.pptxvarshanayak241
Data migration is a complex but essential task for organizations aiming to modernize their IT infrastructure and leverage new technologies. By understanding common challenges and implementing these strategies, businesses can achieve a successful migration with minimal disruption. Data Migration Tool like Ask On Data play a pivotal role in this journey, offering features that streamline the process, ensure data integrity, and maintain security. With the right approach and tools, organizations can turn the challenge of data migration into an opportunity for growth and innovation.
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
5. 5
Neo4j PS Professional Services Offer
Training &
Enablement
Solution Delivery
and Management
Packaged Services
Typically 5-25 days
Neo4j advises
Customer or SI builds
80% of engagements
Custom Scoped
50+ days
Neo4j delivers
Customer or SI supports
20% of engagements
6. PROFESSIONAL
SERVICES
GRAPH ACADEMY
SOLUTIONS
CUSTOMER SUPPORT
● Packaged Services
● Staff Augmentation
● Project/Solution Delivery
● Class room training
● Online/Virtual training
● Certification
● Innovation Labs
● Solution Workshops
● Solutions Development
●24x7x365 & KB
●Platinum support
●Cloud Managed Services
●DBaas (NEW)
●Agile Solution Support
Training
Enablement
Solution Delivery
and Mgmt
Organisation and offerings
13. Solution (Foundation) Framework
Neo4j Graph Platform
Recom
Framework
Custom
App
Solution Foundation Framework
Neo4j Data Orchestrator Framework
Neo4j Deployment Framework Neo4j Managed Service
Fraud
Framework
Network Mgmt
Framework
Custom
App
Custom
App
Custom
App
Custom
App
Custom
App
Neo4j Version Management Service
14. Solution (Foundation) Framework
Neo4j Graph Platform
Recom Telco
App
Solution Foundation
Framework
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers
App App
15. Solution Foundation Framework
Neo4j Graph Platform
Recom Telco
App
Solution Foundation
Framework
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers
App App
API dev
3rd party
graph viz
Custom dev -
graph viz libraries
3rd party
analytics
Python,
Java ML, ...
Kettle
3rd party
DI/EAI
Docker
Kubernetes
Git
Lineage
Kettle
GRANDstack
Apache Kafkaapoc.load.*
25. Where AI and ML fit in
25
Development &
Administration
Analytics
Tooling
Graph
Analytics
Graph
Transactions
Data Integration
Discovery & VisualizationDrivers & APIs
AI
26. Differences between ML and Analytics
26
Machine learning:
• Determine domain parameters
• Historical-based discoveries
• Learn and improve without explicit
programming
27. Graph analytics:
• Uses inherent graph structures
• Uncover real-world networks
through their connections
• Forecast complex network
behavior and identify action
Differences between ML and Analytics
28. Today challenges with Machine Learning:
• Doesn’t take multiple relationship hops into account
• Takes time to iteratively train a model
• Computational inefficiency of connecting data
Benefits of Mixing Graph Analytics with ML
Graphs bring:
• Context to machine learning
• Feature filtration
• Connected feature extraction
29. • Support for many languages (Python,
.Net, Java, Go, JavaScript, R, etc.)
• Different data integration options
• Triggers, event-driven architecture
• User-defined functions and
procedures
Working with your Machine Learning algorithms and Neo4j
30. Pathfinding
& Search
Centrality /
Importance
Communit
y
Detection
Similarity &
ML Workflow
• Parallel Breadth/Depth First
Search
• Shortest Path
• Single-Source Shortest Path
• All Pairs Shortest Path
• Degree Centrality
• Closeness Centrality
• Betweenness Centrality
• PageRank/Personalized PageRank
• Triangle Count
• Clustering Coefficients
• Connected Components (Union Find)
• Strongly Connected Components
• Harmonic Closeness Centrality
• Dangalchev Closeness Centrality
• Wasserman & Faust Closeness
Centrality
• Approximate Betweenness Centrality
• A* Shortest Path
• Yen’s K Shortest Path
• K-Spanning Tree (MST)
• Minimum Spanning
Tree
• Euclidean Distance
• Cosine Similarity
• Jaccard Similarity
• Label Propagation
• Louvain Modularity – 1 Step
• Louvain – Multi-Step
• Balanced Triad
Out of the box Graph Algorithms in Neo4j
• Random Walk
• One Hot Encoding
31. Knowledge graph example:
• Using topic finding ML processes
(e.g. Latent Dirichlet Allocation)
• Feeding the output into a graph database
• Search for topics, find related concepts, etc.
31
Graph and Machine Learning Examples
Recommendation engine example:
• Use ML processes such as collaborative filtering
• Enrich graph with the output
• Use graph as feedback for future iterations
34. Our Neo4j activity implementation has led to a great decrease in complexity, storage, and
infrastructure costs. Our full dataset size is now around 40 GB, down from 50 TB of data
that we had stored in Cassandra. We’re able to power our entire activity feed
infrastructure using a cluster of 3 Neo4j instances, down from 48 Cassandra instances of
pretty much equal specs. That has also led to reduced infrastructure costs. Most
importantly, it’s been a breeze for our operations staff to manage since the architecture is
simple and lean.”
David Fox, Adobe, Oct 2018
34
Customer Quote
How can Neo4j Services help you to get there?
35. Customer Use Case:
• Leading online platform to showcase and discover creative work
• More than 10 million members
• Allows creatives to share their work with millions of daily visitors
• Highlights Adobe software used in the creation process
• Drives people to the Adobe Creative Cloud
• Social platform for discovery, learning, and more
35
Adobe – Project Behance
Activity feed:
• Mongo DB (2011) - 125 nodes, dataset size of about 20tb
(terabytes)
• Cassandra (2015) - 48 nodes, dataset size of about 50tb
(terabytes)
• Neo4j (2018) - 3 nodes, dataset size of 33gb (gigabytes)
5 day
BOOTCAMP
36. 36
Conclusion
• Neo4j PS makes customer projects successful
• through enablement
• through project / solution delivery
• Graph Based Solutions are accelerators for your success
• Neo4j is a good foundation for AI and ML
• Customer are using Neo4j for their success