Hi [[ session.user.profile.firstName ]]

The Spirit of the City: Capturing Network-Generated Data for Better Cities

The corporate smart-city rhetoric is about efficiency, predictability, and security. "You'll get to work on time, no queue when you go shopping, and you are safe because of CCTV cameras around you". All these things make a city acceptable, but they don't make a city great.

Goodcitylife.org is a global group of like-minded people who are passionate about building technologies whose focus is to give a good life to city dwellers; because the future of the city is, first and foremost, about people.

We go beyond the creation of a smart city by using digital data to measure intangible aspects of the urban space: the spirit of the city. We will show how this acquired knowledge can be leveraged to build new tools for both citizens and municipalities. Can we rethink existing mapping tools? Is it possible to capture smellscapes of entire cities and celebrate good odors? Can you measure a city's cultural capital?

We will see how a creative use of network-generated data can tackle hitherto unanswered research questions.
Recorded Jul 3 2019 20 mins
Your place is confirmed,
we'll send you email reminders
Presented by
Luca Maria Aiello, Senior Research Scientist, Nokia Bell Labs
Presentation preview: The Spirit of the City: Capturing Network-Generated Data for Better Cities

Network with like-minded attendees

  • [[ session.user.profile.displayName ]]
    Add a photo
    • [[ session.user.profile.displayName ]]
    • [[ session.user.profile.jobTitle ]]
    • [[ session.user.profile.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(session.user.profile) ]]
  • [[ card.displayName ]]
    • [[ card.displayName ]]
    • [[ card.jobTitle ]]
    • [[ card.companyName ]]
    • [[ userProfileTemplateHelper.getLocation(card) ]]
  • Channel
  • Channel profile
  • Crash Course in Data Architecture Dec 17 2019 2:00 pm UTC 44 mins
    Jesse Bishop, Solutions Architect, Dataiku & Christina Hsiao, Tech Evangelist, Dataiku
    Data architecture is the foundation of every organization’s data strategy, but it's not just something for CIOs and data architects either - everyone at data-powered organizations can benefit from understanding the ways data moves between teams and flows into data projects to yield insights. In our Crash Course, we’ll cover key architecture terms and highlight different priorities regarding security and scalability. Additionally, we’ll discuss ways to strategize and align architectural concerns with business priorities.

    Jesse Bishop works with a wide variety of Fortune 500 clients and specializes in helping large organizations operationalize their AI workflow. Jesse is an Insight Data Science Fellow in New York City. He previously worked for the Federal Trade Commission developing models to predict the impact of mergers in a wide variety of industries including Energy, Semiconductors, and E-commerce. Jesse earned his Ph.D. in Applied Microeconomics from the University of Minnesota.

    Christina Hsiao is a technical evangelist for Dataiku based in the US. In her role, Christina is able to share her passion for applied data science through writing and by speaking with customers, partners, and organizations interested in solving business problems with the powerful combination of people, data, and technology. Prior to joining Dataiku, she spent nearly a decade at SAS, mainly specializing in Natural Language Processing and text analytics. Christina holds a bachelor’s degree in Mechanical Engineering from Stanford University.
  • AI in Finance: The Current Landscape, What the Future Holds, the Role of Fintech Dec 12 2019 2:00 pm UTC 56 mins
    Alexandre Hubert, Lead Data Scientist at Dataiku
    Enterprise AI is at peak hype, yet AI has yet to fundamentally change most businesses - BFSI market is no exception.

    Fintech has swept in and remains on the cutting-edge of the AI and the finance spaces simultaneously, offering tough competition for those savvy enough to try and catch up. Yet there are some success stories beginning to emerge in large, traditional organizations (outside the fintech space) with learnings and takeaways for others ready to dive in.

    Specifically, this webinar will cover:

    - What fintechs bring to the table that makes them successful.
    - Recent use cases and successes in AI by traditional financial institutions.
    - What, on a wider level, has proved successful for traditional players and how it can be leveraged by your organization.
  • 5 Steps to Building Responsible AI Systems (featuring Forrester) Dec 2 2019 2:00 pm UTC 63 mins
    Kurt Muehmel, VP of Sales Engineering at Dataiku, and guest Mike Gualtieri, VP and Principal Analyst at Forrester
    Responsible AI is essential for any company that wants to have robust AI systems in place in the future.

    This webinar will cover the essential steps to building AI systems that are responsible. But what does responsible AI mean? For a start, it’s about:

    - Making sure that systems are centralized for control over data yet flexible enough to allow for innovation.
    - Ensuring that robust monitoring is in place for all models.
    - Establishing trust in people and in data.
    - A company-wide dedication to models that are interpretable, unbiased, and ultimately won’t cause PR and trust issues for the company down the line.
    ...and more.

    Kurt Muehmel, VP of Sales Engineering at Dataiku, and guest Mike Gualtieri, VP and Principal Analyst at Forrester, will discuss the ins and outs of all of these topics (and more) for the first portion followed by a Q & A at the conclusion of the presentation. You’ll want to make sure to catch this webinar live for a chance to ask your questions about bringing responsible AI to your enterprise.
  • How to Achieve Big Data Insights Without Sacrificing Privacy Nov 26 2019 2:00 pm UTC 43 mins
    Anjan Roy & Jamil Siddiqui of Deloitte Consulting | Jeremy Greze of Dataiku
    In today’s landscape with data privacy laws cropping up worldwide, some data teams have become paralyzed by uncertainty in how to navigate this new world. But armed with a productive governance strategy, organizations and individuals (from the data analyst to data scientist and IT professional) can continue to move forward in getting value out of data without compromising individuals’ privacy.

    This webinar will answer the following questions:

    - What are the biggest challenges of today’s data privacy landscape (and how can they be addressed)?
    - What are the best practices for using data while also remaining compliant?
    - How can organizations create access-controlled environments and easily handle right-to-erasure requests?

    Anjan Roy and Jamil Siddiqui, Managing Director and Specialist Leader at Deloitte consulting, along with Dataiku product manager Jeremy Greze will answer these questions by offering strategies for leveraging people, processes, and technology.
  • Top 5 data science challenges & opportunities in Financial Services Nov 19 2019 2:00 pm UTC 48 mins
    Grant Case of Dataiku interviews Victor Tewari of BMO Capital and Jimmy Steinmetz of Interworks
    We surveyed more than 50 global data & analytics leaders about their top challenges for 2019.

    The results reveal that there are still fundamental challenges to leveraging AI and machine learning at scale.

    In this webinar, we sit down with banking data leaders to cut through the hype and discuss the real barriers and opportunities towards discovering value in data in 2019.

    We reveal and discuss those opportunities and challenges with Victor Tewari, Technology Officer in Predictive Analytics at BMO Capital and Jimmy Steinmetz, Solution Lead at InterWorks.

    This live event will be ideal for technical and non-technical audiences alike. If you can’t make the live time, register anyways and the recording will be sent to your inbox.
  • How Machine Learning Helps Levi’s Leverage Data to Enhance E-Commerce Experience Nov 18 2019 4:00 pm UTC 71 mins
    An AWS and Dataiku Partnership
    Levi Strauss & Co. (Levi’s) had already migrated its store and data science applications to the cloud. It needed a way to quickly create prototypes and put them into production to create different meaningful customer experiences on the website.

    Levi’s used Dataiku Data Science Studio (DSS) and Amazon Web Services (AWS) to create a recommendation system that aligns to a customer journey, such as showing best-selling products in their region to new customers or displaying complementary items to complete an outfit to returning purchasing customers.

    Watch this webinar to learn how machine learning enables Levi’s to easily and quickly leverage its data to create new products for its customers.

    Watch to learn how to:

    - Try different algorithms and ways of connecting data together through data pipelines to move beyond experimentation into operations
    - Use Amazon SageMaker for model training
    - Create prototypes in Dataiku DSS and use AWS to put them into production
    - Run multiple processes in parallel
  • Discover Applied Deep Learning Basics Nov 14 2019 2:00 pm UTC 51 mins
    Andrey Avtomonov, R&D Engineer at Dataiku & Rodrigo Agundez, Data Scientist at GoDataDriven
    Deep Learning models can be exceedingly powerful and accurate if you are willing to invest the time to train them. However, there’s no need to waste energy on poorly framed problems or building model architecture from the ground up. In this webinar, with GoDataDriven, we’ll reveal the best practices we’ve learned from leveraging Deep Learning in a variety of real-world systems, in addition to showing you how to access Deep Learning quickly, so that you can spend time personalizing your model to provide the best business value for your unique needs.

    Per registering to this webinar, you agree to get one email from GoDataDriven afterwards
  • Machine Learning Basics: Algorithms Are Your Friend Recorded: Nov 5 2019 45 mins
    Katie Gross, Data Scientist
    Machine learning (ML) isn’t just for data scientists anymore; it’s in the mainstream for analytics and business teams who want to get ahead, but it can feel impenetrable. Where to start? Join Dataiku Data Scientist Katie Gross as she outlines key machine learning terms and the applications of different ML algorithms. See how you can build and evaluate an ML model with or without coding. Watch live and ask questions at our Q&A at the end of the talk.

    Katie Gross is a Data Scientist at Dataiku, where she helps clients build out Enterprise AI solutions and develops new product features. Previously, she worked as a data scientist at a marketing science firm, Schireson, and did freelance data science work for a host of companies including IBM. Prior to her data science life, Katie spent three years as a CPG consultant to Wall Street analysts at Nielsen. Katie holds a BA in Economics from Colgate University and also completed the Galvanize Data Science Bootcamp program in New York City.
  • 2019 AI Trends: Filtering the Noise Recorded: Nov 5 2019 32 mins
    Leo Dreyfus-Schmidt, Dataiku AI Labs Lead Scientist
    Learn about the AI trends in 2019 - what will matter in the year to come, and what won't. Leo Dreyfus-Schmidt, Dataiku AI Labs Lead Scientist, will present his take on technologies to watch as a data scientist.

    This presentation will be ideal for technical and non-technical audiences alike.
  • Profit from AI and machine learning—The best practices for people and process Recorded: Oct 30 2019 61 mins
    Florian Douetteau, CEO, Dataiku; Tony Baer, Principal Analyst, Ovum
    For projects employing machine learning or deep learning, the acid test doesn’t come from making that first “win.” Instead, the true test is making successes from embracing AI consistent and repeatable. Like most new technology innovations, for AI, the spotlight has initially been on the technology. Because the AI practice in the enterprise is still in its infancy, there is less knowledge about the “soft” side: understanding how to build the teams of people that make AI happen and creating the processes that can make success repeatable.

    Dataiku and Ovum are collaborating on a jointly sponsored primary research study to address the knowledge gap on “the soft side” of making AI work for the business, conducting a qualitative survey of specially selected leaders and practitioners in the field, including chief data officers, chief officers and directors of data science, and chief officers and directors of analytics. Tony Baer and Florian Douetteau summarize the lessons learned from this research and identify best practices for ingraining AI into the business, based on actual experience in the field.
  • Società data-driven & IA: self-service analytics e operazionalizzazione dei dati Recorded: Oct 22 2019 46 mins
    Hugo Owen (deployment strategist), Erica Maccaferri (big data analyst) and Luca Guerra (big data analyst)
    Molte organizzazioni cercando di diventare data-driven si pongono la domanda:
    Raggiungeremo i nostri obiettivi tramite l'analisi self-service oppure tramite la messa in produzione dei risultati? La risposta è: attraverso il giusto equilibrio di entrambe!
    Infatti, se a prima vista le due attività sembrano essere lontane, in realtà completano insieme la data strategy aziendale. Grazie ad un veloce e frequente passaggio tra analisi self-service (SSA) e messa in produzione (o16n) un'azienda può diventare realmente data-driven operando in tutti i progetti al massimo del suo potenziale.

    Unisciti al webinar ospitato da Dataiku e BitBang per vedere come implementare una data strategy completa che veda la presenza di entrambe le attività evitando così gli errori più comuni.

    Relatori:
    - Hugo Owen, deployment strategist presso Dataiku
    - Erica Maccaferri, Big Data analyst presso BitBang
    - Luca Guerra, Big Data analyst presso BitBang

    Iscrivendoti a questo webinar, acconsenti che le tue informazioni possano essere condivise con il partner di Dataiku BitBang.
  • How to Thrive in the Enterprise AI Era | by Forrester & Dataiku Recorded: Oct 21 2019 59 mins
    Guest Speaker Mike Gualtieri, VP & Principal Analyst @ Forrester & Florian Douetteau, CEO@ Dataiku
    The year 2018 was supposed to be a banner one for artificial intelligence (AI) in the enterprise. But more and more, companies are finding that Enterprise AI is much easier talked about than executed. And there are still a fair number of open questions that need to be answered to move forward and excel in the Enterprise AI era, like:

    - What exactly does it mean to do Enterprise AI anyway (and how is it different from regular AI)?
    - How does Enterprise AI connect to machine learning and deep learning (and what's the difference)?
    - What are the challenges, risks, and benefits to getting started on Enterprise AI now?

    This webinar will answer these pressing questions.

    Presented in a conversational format, Mike Gualtieri, VP & Principal Analyst at Forrester, and Florian Douetteau, CEO at Dataiku, will address these points by way of case studies (i.e., what real companies are doing right now in this space) plus discuss how those who haven't started can dive in.
  • Crash Course in Data Architecture Recorded: Oct 16 2019 45 mins
    Jesse Bishop, Solutions Architect, Dataiku & Christina Hsiao, Tech Evangelist, Dataiku
    Data architecture is the foundation of every organization’s data strategy, but it's not just something for CIOs and data architects either - everyone at data-powered organizations can benefit from understanding the ways data moves between teams and flows into data projects to yield insights. In our Crash Course, we’ll cover key architecture terms and highlight different priorities regarding security and scalability. Additionally, we’ll discuss ways to strategize and align architectural concerns with business priorities.

    Jesse Bishop works with a wide variety of Fortune 500 clients and specializes in helping large organizations operationalize their AI workflow. Jesse is an Insight Data Science Fellow in New York City. He previously worked for the Federal Trade Commission developing models to predict the impact of mergers in a wide variety of industries including Energy, Semiconductors, and E-commerce. Jesse earned his Ph.D. in Applied Microeconomics from the University of Minnesota.

    Christina Hsiao is a technical evangelist for Dataiku based in the US. In her role, Christina is able to share her passion for applied data science through writing and by speaking with customers, partners, and organizations interested in solving business problems with the powerful combination of people, data, and technology. Prior to joining Dataiku, she spent nearly a decade at SAS, mainly specializing in Natural Language Processing and text analytics. Christina holds a bachelor’s degree in Mechanical Engineering from Stanford University.
  • Use Case Demo: Machine Learning Based Fraud Detection Recorded: Oct 1 2019 44 mins
    Kevin Graham, Advanced Technology Strategist for Financial Services, and Will Nowak, Solutions Architect
    Fraudulent actors are always looking for new ways to subvert legitimate transaction systems; traditional rules-based approaches are no longer sufficient (or efficient enough) to combat fraud. In this webinar, we’ll discuss best practices and examples on how machine learning can improve fraud detection capabilities.

    Data Scientists, Quants, and Analysts in the banking sector can benefit from expert best practices on tackling fraud detection. We’ll include a brief use case demo to concretely ground the discussion and discuss real-time considerations for detection. Kevin’s financial expertise and Will’s diverse implementation experience make them the perfect team to explore the host of factors that go into a machine learning fraud detection model. We’ll host a Q&A after the demo, so make sure to join us live.

    Kevin Graham is a Dataiku Account Executive with nearly 10 years of experience across financial services and technology. He started his career in Sales & Trading before moving into a technology sales capacity at Oracle and Merlon Intelligence. At Merlon, Kevin focused on how AI and machine learning could help solve complex challenges within financial crime compliance. He currently is part of a financial services focused sales team across the Eastern United States and Canada at Dataiku.

    Will Nowak is a solutions architect at Dataiku, where he helps Fortune 500 companies improve data science operations. Previously, he engineered machine learning models for several Y Combinator startups, learning the pitfalls and challenges to productionalizing machine learning. Will holds a bachelor’s in Math and Economics from Northwestern University and a Master’s in Organizational Leadership from Columbia University.
  • How Machine Learning Helps Levi’s Leverage Data to Enhance E-Commerce Experience Recorded: Sep 19 2019 72 mins
    An AWS and Dataiku Partnership
    Levi Strauss & Co. (Levi’s) had already migrated its store and data science applications to the cloud. It needed a way to quickly create prototypes and put them into production to create different meaningful customer experiences on the website.

    Levi’s used Dataiku Data Science Studio (DSS) and Amazon Web Services (AWS) to create a recommendation system that aligns to a customer journey, such as showing best-selling products in their region to new customers or displaying complementary items to complete an outfit to returning purchasing customers.

    Watch this webinar to learn how machine learning enables Levi’s to easily and quickly leverage its data to create new products for its customers.

    Watch to learn how to:

    - Try different algorithms and ways of connecting data together through data pipelines to move beyond experimentation into operations
    - Use Amazon SageMaker for model training
    - Create prototypes in Dataiku DSS and use AWS to put them into production
    - Run multiple processes in parallel
  • Data Transformation at GE Aviation Recorded: Aug 26 2019 19 mins
    Somesh Saxena and Jon Tudor, GE Aviation
    GE Aviation has implemented their own version of a self-service data system that now has more than 1,800 users throughout the company, allowing them to use real-time data at scale to make better and faster decisions throughout the organization.

    This webinar is a Q&A format with Jon Tudor, Sr. Manager Self-Service Data and Analytics and Somesh Saxena, Product Owner of Dataiku and Alation, at GE Aviation. It covers the how and why behind the company's data transformation.
  • Defining ROI for Data Initiatives Recorded: Jul 30 2019 42 mins
    Mike Bukowski, VP Sales, Dataiku
    Calculating the Return on Investment (ROI) of your data initiatives is critical to activating your data; if you can't show that data initiatives are valuable, there will be resistance across the organization to implementation, causing you to miss out on opportunities and lag behind the competition. ROI isn't a simple calculation, but rather one that requires an in-depth understanding of your business needs and pain points. Mike has years of experience demonstrating the value data initiatives can unlock and will share tips, tricks, and best practice guidelines for helping you understand your own ROI metrics.
  • EGG London 2019 Highlights Recorded: Jul 16 2019 3 mins
    Dataiku
    Take a look at the best of EGG 2019 London!
  • Toward Ethical AI: Inclusivity as a Messy, Difficult, but Promising Answer Recorded: Jul 5 2019 15 mins
    Larry Orimoloye, Solutions Architect, Dataiku
    AI technologists must consider the ethical implications of what we’re building. Kurt Muehmel explores AI within a broader discussion of the ethics of technology, arguing that inclusivity and collaboration is a necessary answer.
  • GDPR and the ICO's Proposed AI Auditing Framework Recorded: Jul 5 2019 26 mins
    Ali Shah, Head of Technology Policy, Information Commissioner's Office
    The use of AI in industry and society is growing, and so are the concerns about its impact. The Information Commissioner’s Office (ICO) is responsible for protecting individual’s data protection rights, and has been at the forefront of tackling complex privacy challenges with significant societal implications, including the Facebook/Cambridge Analytica investigation for example.

    The ICO has made AI a priority for the organisation and, with the new powers given to us through the GDPR, we are developing an enhanced supervisory framework for assessing the risks and potential harms to peoples’ data protection rights that could occur when AI is used. The framework will cover many of the hot risk topics which are the focus of the EGG conference, including interpretability, bias, and fairness among others.

    This talk will inform the audience about the ICO’s work on AI, give an overview of our current thinking on some of the steps organisations can take to navigate AI’s data protection challenges, and encourage the audience to feed into the framework’s ongoing consultation.
Dataiku
Dataiku is the centralized data platform that moves businesses along their data journey from analytics at scale to enterprise AI. By providing a common ground for data experts and explorers, a repository of best practices, shortcuts to machine learning and AI deployment/management, and a centralized, controlled environment, Dataiku is the catalyst for data-powered companies.

Customers like Unilever, GE, BNP Paribas, Santander use Dataiku to ensure they are moving quickly and growing exponentially along with the amount of data they’re collecting. By removing roadblocks, Dataiku ensures more opportunity for business-impacting models and creative solutions, allowing teams to work faster and smarter.

Embed in website or blog

Successfully added emails: 0
Remove all
  • Title: The Spirit of the City: Capturing Network-Generated Data for Better Cities
  • Live at: Jul 3 2019 9:30 am
  • Presented by: Luca Maria Aiello, Senior Research Scientist, Nokia Bell Labs
  • From:
Your email has been sent.
or close