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EGG On-Demand: The 7 Powers of Machine Learning

In this talk, Lucas Bernardi, Principal Data Scientist at Booking, introduces The 7 Powers of Machine Learning, a tool to help product teams to make the most out of this amazing technology, and showcasse how they successfully use it at Booking.com.
Recorded May 15 2020 29 mins
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Presented by
Lucas Bernad, Principle Data Scientist @ Booking
Presentation preview: EGG On-Demand: The 7 Powers of Machine Learning

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  • Establish Data Advocacy in Your Organization with WeWork Apr 2 2021 6:00 pm UTC 75 mins
    Lucianne Millan (Data Engineering Manager at WeWork)
    Tentative Schedule: (EST)

    2:00pm: Intro
    2:05pm: Establish Data Advocacy in Your Organization with WeWork
    2:45pm: Q&A

    Talk Abstract:

    Data has minimal impact without adoption from the everyday user. To create an authentically data-driven organization top down, it is essential to gain buy-in from stakeholders and share the skills required for analysis in a scalable way. At WeWork, we have a high volume of users on local and global levels. In this session we will provide the framework for how to establish data advocacy in your organization, revolving around our 3 pillars of data culture- awareness, trust and empowerment.

    Speaker Bios:

    Lucianne is a Data Engineering Manager at WeWork, where she has spent the last 3 years helping to bridge the gap between insights and business impact, with a special focus on enabling data-driven decision making for executives and investors. She has over 10 years of professional experience in data, spanning different industries, company sizes and data disciplines. She is passionate about promoting data literacy and works with institutions such as Columbia University and Parsons to design and teach data skills at a graduate level.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
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    Join us for this Dataiku session, where we will reconstruct an equity index fund and rebalance based on analysis. We'll also look at building a Monte Carlo-based intrinsic value calculator for an underlying asset. Lastly, these data products will then be surfaced through a Dataiku app and a webapp for broader consumption.
  • Recommendation Systems for B2B Companies Mar 31 2021 2:00 pm UTC 75 mins
    Yiwei Li (Data Scientist @Paypal)
    Tentative Schedule: (EST)

    10:00am: Intro
    10:05am: Recommendation Systems for B2B Companies w/ Yiweil Li (Paypal)
    10:45am: Q&A

    Talk Abstract:

    TBD

    Speaker Bio:

    Yiwei is currently a data scientist at PayPal. Previously, Yiwei was a Sr. Analytics Consultant in Machine Learning at EXL where she facilitated the underwriting decision-making program for J.P Morgan Chase’s small business loan applications by optimizing between revenue objectives and risk management. She graduated from Columbia University with a Master’s degree in Statistics.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
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    Alexander Rode, Analyst Data and Analytics, BARC
    In this webinar, BARC Analyst and Data Scientist Alexander Rode will give you a brief insight into the results of the recent BARC study "The Future of Analytics". 

    During the webinar, we will cover the following aspect/section of the study: 

    1) Data analytics and the associated expectations
    2) The current state of Advanced Analytics
    3) Latest trends in the software market, such as AutoML and Augmented Analytics

    Based on the findings of the study, our speaker will give some recommendations that will help companies to implement advanced analytics.
  • Defining a Successful AI Project: A Framework for Choosing the Right AI Use Case Mar 22 2021 6:00 pm UTC 49 mins
    Christina Hsiao, Sales Engineer/Evangelist at Dataiku and Vivien Tran-Thien, Director of AI Consulting at Dataiku
    With dozens of ideas for potential AI use cases but limited time and resources, how can organizations prioritize the right projects…especially in the early stages of their Enterprise AI journey?

    In this talk, Christina Hsiao and Vivien Tran-Thien from Dataiku will help you ask the right questions to identify projects that have both high business value and a high likelihood of success. The framework outlined in this webinar will help you avoid false starts on AI initiatives that are risky or ill-defined, and instead create a blueprint for future success!
  • Machine Learning Basics: Algorithms Are Your Friend Mar 18 2021 6:00 pm UTC 44 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.
  • Operationalization and Deployment: Building Production-Ready AI Projects Mar 17 2021 6:00 pm UTC 30 mins
    Alexandre Hubert, Lead Data Scientist, Dataiku
    How to build production-ready data science projects?
    How to transition from a design to a production environment?

    Designing and validating models is only one part of a whole data science project.

    And today production issues are the main reason many companies fail to see real benefits come from their data science efforts.

    During this webinar, we will first understand what « to go into production » means and then consider actionable steps to build production-ready data science projects:

    1. Operationalisation: why is it important?
    2. Challenges from design to production
    3. Building production-ready AI projects
  • Accelerate Automation with AI Capturing Mar 11 2021 10:00 am UTC 60 mins
    Christophe Hocquet, Co-Founder at Natif.ai
    Accelerate Automation with AI Capturing

    Every business needs to manage, control and connect its documents. But manual or semi-automated processes are tedious and very costly for enterprises. In this webinar in partnership with Natif.ai, we will explore strategies that enable speed processing of documentation, and improving productivity, avoiding mistakes, reducing technology costs, all using AI Capturing. Register now to join us live.

    Speaker details:
    -Christophe Hocquet, Co-Founder at Natif.ai

    Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Natif.ai. They may contact you with information that could be of interest to you.
  • AI Myths Debunked: Build vs. Buy your AI platform Mar 11 2021 3:00 am UTC 30 mins
    Ryan Morris, Account Executive, Dataiku
    In the world of data science, machine learning, and AI, there is no shortage of tools — both open source and commercial — available. This inevitably spurs the age-old software question of build vs. buy for AI projects and platforms.


    During this session, Ryan Morris, Account Executive at Dataiku, will address the following:

    > Is the question to make or buy models?
    > Data processing tools?
    > 6 key considerations that should be tabled when evaluating whether to build or buy your AI platform
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    Hervé Mignot (Equancy), Raphaël Hamez (Equancy)
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    In this webinar, we introduce:
    -Key notions of MLOps practices
    -Highlight classical difficulties & roadblocks of data science use case life cycle.

    We present MLOps practices, illustrate these elements through actual use cases, and how Dataiku DSS can support such MLOps practices.

    Speakers:
    -Hervé Mignot, Data Science, Technologies and R&D Partner @ Equancy
    -Raphaël Hamez, Lead Data Scientist @ Equancy

    Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Equancy. They may contact you with information that could be of interest to you.
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    Ju Yang (Machine Learning Engineer at Spotify)
    Tentative Schedule: (EST)

    4:00pm: Intro
    4:05pm: How Spotify Drives Audio Monetization with ML
    4:45pm: Q&A

    Talk Abstract:

    Audio presents a unique marketing opportunity for advertisers and a valuable monetization opportunity for creative artists. Spotify, with its wide and diverse audio content including music and podcasts, is building an audio ad platform to connect millions of brands and marketers to billions of fans so that creators can continue to live off their work and listeners can enjoy it. In this talk, I will share how we use ML to personalize user experience, optimize advertiser outcomes, and drive audio monetization.

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    Ju Yang is a Machine Learning Engineer at Spotify. She is currently working on the advertising machine learning team. She applies machine learning and engineering to drive ad performance and audio monetization. Prior to Spotify, Ju worked at Tapad, an adtech company in New York. Ju received her bachelor degree from Tsinghua University in China, and PhD in Neuroscience from Columbia University. In her spare time, Ju likes watching Sci Fi movies, writing blogs and making YouTube videos on tech careers and machine learning.

    Disclaimer: All views, thoughts, & opinions expressed in the webinar belong solely to the panelists, & not to the panelists’ employer, organization, committee, other group or individual.
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    Thayer Adkins - Director of Partnerships @ Dataiku and Frederick DeWorken - Director of Latin America at Snowflake
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    Participa En Este Webinar En Vivo:

    En nuestra presentación verán como un DBA y un científico de datos ‘ciudadano’ podrán fácilmente colaborar en un proyecto desde la identificación e ingesta de datos hasta modelamiento y aplicación de técnicas de machine learning. Verán lo mismo en una demostración destacando cómo podrán lograr con un simple equipo de dos el despliegue de un proyecto de ciencia de datos colaborando en una plataforma y comunicando los resultados a otros compañeros.
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    The event will feature a 15-20 minute Q&A session, so be sure to join live and come with questions for the experts!
  • Leverage AI in Manufacturing: Predictive Maintenance Recorded: Feb 23 2021 41 mins
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    Leveraging AI is an efficient way to provide real-time visibility into the production process to reduce downtime for maintenance and costs for efficient operations. Join us as we walk through how sensor data can be transformed to timely insights via predictive maintenance with automated insight improvement.

    During this webinar, we will:
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    - Determine when purchased equipment might fail to deploy resources to service customers
    - Look at root cause analysis and model drift.
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    Katie Gross, Lead Data Scientist @ Dataiku
    Natural Language Processing (NLP), the branch of machine learning and AI which deals with bridging the gap between human language and computer understanding, is all the rage right now. Once a relatively niche topic, in the past few years landmark new models and applications have brought NLP to the center-stage of real-world enterprise data science and AI.

    This webinar will give data scientists a framework for getting started with NLP projects. It will go over:
    • What exactly NLP is and how it’s used
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    • An overview of some of the main NLP algorithms and how they work

    Katie Gross is a Lead Data Scientist at Dataiku, where she helps clients across industries develop AI solutions using Dataiku DSS. Previously, she worked as a data scientist at a marketing science firm, Schireson and did freelance data science work for IBM and a dating app, Radiate. Prior to her data science life, Katie spent three years as a CPG consultant at Nielsen. Katie holds a BA in Economics from Colgate University.
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Your Path to Enterprise AI
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.

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  • Live at: May 15 2020 2:15 pm
  • Presented by: Lucas Bernad, Principle Data Scientist @ Booking
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