Want to judge whether your recipe will be a hit? Or in general, what user-generated content is likely to lead to high engagement? This Dataiku Community on-demand talk will walk you through the basics of text pre-processing and using NLP to predict which recipes are likely to be highly rated. By the end of the talk, viewers should be able to take away the reasoning and key steps of the project and apply NLP to their own prediction problems.
RecordedApr 8 202027 mins
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Every business needs to manage, control and connect its documents. But manual or semi-automated processes are tedious and very costly for your enterprise. Using our AI will help you to increase speed processing, avoid mistakes, reduce technology costs and immediately improve productivity.
Join our live webinar in partnership with Natif.ai.
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.
Gartner Senior Director Saniye Alaybeyi & Dataiku Chief Customer Officer Kurt Muehmel
Myth: AI and ML are the same and interchangeable.
Myth: AI is all about deep learning.
Myth: All black-box AI needs to be explainable.
Myth: AI is an unnecessary luxury in times of economic crisis.
Myth: AI can be free of bias.
Join Gartner Senior Director Saniye Alaybeyi & Dataiku Chief Customer Officer Kurt Muehmel in this fireside chat-style virtual event as they discuss these myths about AI (and more) plus up-and-coming trends for AI in 2021 and beyond.
The event will feature a 15-20 minute Q&A session, so be sure to join live and come with questions for the experts!
7:00pm: Intro
7:05pm: Recommendation Systems for B2B Companies w/ Yiweil Li (Paypal)
7:45pm: 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.
Dataiku AI Lab Research Director Léo Dreyfus-Schmidt & Team
This technical webinar presented by research scientists at the Dataiku AI Lab will feature a discussion of the year's hottest topics in machine learning research and what's to come in 2021.
Sandeep Deshmukh (HPE), Dietrich Zinsou (HPE), Daniel Hladky (Dataiku)
Enterprises are facing challenges with operationalizing their ML models as they move from PoCs to production.
The emerging field of ML Ops – machine learning operations – aims to deliver agility and speed to the ML lifecycle similar to what DevOps processes have done for the software development lifecycle.
In this webinar, we will discuss how to:
- Overcome the barriers of deploying and operationalizing ML models
- Gain faster time-to-value, increase productivity, and reduce risk with a flexible end-to-end ML Ops solution
- Deploy and access data more efficiently whether on premises, in the cloud, or a hybrid environment
Join this webinar to learn how Dataiku and HPE are bringing speed and agility to the ML lifecycle.
Speakers:
- Sandeep Deshmukh, Product Manager ML Ops at Hewlett Packard Enterprise
- Dietrich Zinsou, Senior Solutions Architect at Hewlett Packard Enterprise
- Daniel Hladky, Senior Partner Manager at Dataiku
Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Hewlett Packard Enterprise. They may contact you with information that could be of interest to you.
Conor Jensen, Director of AI Consulting at Dataiku
This non-technical webinar will go in-depth on the trends that will continue to dominate Enterprise AI, particularly when it comes to organizational changes in businesses.
Charlie Lovett-Turner(Natwest Markets), Hadrien Servy(Dataiku) and Puneetha Bagivalu Manjegowda(Deloitte)
This webinar features Dataiku's session from Deloitte's Experience Analytics 2020 Virtual Series. Presented to you by Deloitte, NatWest Markets and Dataiku, it showcases a reflection on the challenges of modernising the trading floor, and delves deeper into how to harness the technical capabilities of a highly-quantitative workforce.
In an age of technology, the trading floor has remained remarkably resistant to change. Electronification has made significant inroads into equity and FX markets but the concept of sales-client relationships and trading books managed by traders has been very resilient. Join us to takeaway the most exciting trends and practices to tackle these situations with the power of Data and Analytics.
Every manufacturing process from design, production, to supply chain logistics can be optimized with AI. Collaborative modeling throughout the entire chain of production can lead to significantly higher returns including optimized machine settings and improved fault detection to facilitate innovation and improve yield.
In this webinar, we walk through inter-process collaboration, team orchestration, and dive deep into iterative cross-team modeling to see how your organization can leverage the power of AI to optimize the entire lifecycle of product development.
Jesus Oliva, Sr Data Scientists, Marie Vollmar, Enterprise AI Strategist
Take a closer look at the use of data science in financial forecasting with European Association of Corporate Treasurers Award Winners JTI and learn how they improved forecast accuracy by 20%, while reducing their workload as much as 80%!
Garrett Smith, Kartikeya Upasani, Dr. Madiha Jafri
Tentative Schedule: (EST)
2:00pm: Intro
2:05pm: What To Expect of Machine Learning and AI in 2021 [Panel]
2:45pm: Q&A
Talk Abstract:
From leading-edge medical diagnostic systems to consumer electronics and “smart” home assistants, Artificial Intelligence is a critical technology that is changing how we live, work, and play. As we round out a turbulent 2020 and look towards the future, it’s undeniable that AI will continue to play a massive role in restructuring the way many of us handle business and communications. In this Virtual Meetup, we will be joined by a panel of Artificial Intelligence and Machine Learning specialists who will review the current state of the Artificial Intelligence industry in 2020 and forecast what to expect in the near future.
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.
Dataiku AI Lab Research Director Léo Dreyfus-Schmidt & Team
This technical webinar presented by research scientists at the Dataiku AI Lab will feature a discussion of the year's hottest topics in machine learning research and what's to come in 2021.
Suresh Vadakath, Financial Services Sales Engineer at Dataiku
In this talk, Suresh Vadakath, financial services sales engineer at Dataiku, will demonstrate how he leverages Dataiku DSS to mine data using Principal Component Analysis (PCA) to evaluate equities for portfolio construction. From there, he will review how to balance risk versus return while being ESG-conscious in portfolio optimization.
Dataiku is a leading end-to-end, collaborative data science platform that enables technical and non-technical users to collaborate on building data science and analytics projects to aid data-driven decision making across the enterprise.
Léo Dreyfus-Schmidt (directeur de la recherche) et Vivien Tran-Thien (directeur pour les activités de conseil) @Dataiku
Lors de ce webinar, Léo Dreyfus-Schmidt (directeur de la recherche) et Vivien Tran-Thien (directeur pour les activités de conseil) de Dataiku feront un tour d’horizon de tendances émergentes en apprentissage automatique avec des applications intéressantes pour le monde de l’entreprise. Ils évoqueront des questions comme :
> Comment entraîner des modèles lorsqu’on dispose de peu de données ?
> Peut-on détecter et atténuer les biais algorithmiques ?
> Au-delà de formuler des prédictions, peut-on établir des liens de causalité ?
> Comment surveiller et maintenir les performances d’un modèle en production ?
Suresh Vadakath, Financial Services Sales Engineer at Dataiku
In this talk, Suresh Vadakath, financial services sales engineer at Dataiku, will demonstrate how he leverages Dataiku DSS to mine data using Principal Component Analysis (PCA) to evaluate equities for portfolio construction. From there, he will review how to balance risk versus return while being ESG-conscious in portfolio optimization.
Dataiku is a leading end-to-end, collaborative data science platform that enables technical and non-technical users to collaborate on building data science and analytics projects to aid data-driven decision making across the enterprise.
Xavier Maréchal (Reacfin), Samuel Mahy (Reacfin), Julien Antunes Mendes (Reacfin)
Standardization and Improvements of Data Analytics Projects for Financial Institutions
Data Analytics is a hot topic for many financial institutions. Making the most of their data and becoming data driven companies is a strategic differentiator.
In this webinar, we identify practical difficulties in running relevant data analytics projects in financial institutions. Starting from typical projects (e.g. product pricing and behavioral modeling in banks and insurance), we explore some of these difficulties and provide practical solutions to implement a relevant data science pipe-line in financial institutions. We build a standardized approach along with the following steps:
-Business problem framing
-Data Management
-Modelling
-Deployment
-Monitoring
With some additional focus on the communication around data analytics projects and governance aspects. We advocate how data science platforms can help in robustifying this process, decreasing risks and increasing efficiency and added value of data analytics projects.
Speakers:
- Xavier Maréchal, CEO at Reacfin
- Samuel Mahy, Director at Reacfin
- Julien Antunes Mendes, Manager at Reacfin
Please be aware that by registering for this webinar, you agree to have your personal information shared with both partners Dataiku and Reacfin. They may contact you with information that could be of interest to you.
2:00pm: Dataiku x Bots & AI Intro
2:05pm: Navigating the Tricky Process of Becoming A Data Scientist w/ BMW
2:45pm: Q&A
Talk Abstract:
So you want to be a data scientist? Seems like everyone is typing that into Indeed. What does it actually mean to land your first role? How do you transition to data science from a different field? What does it take to be successful once you’re hired?
I’m not going to bore you with the tech stack requirements (although we’ll touch on this), but I’ll mainly focus on what I’ve learned though my own experience breaking into the field, and now as a hiring manager for data science interns.
Speaker Bio:
Dr. Natalie Morse is a data scientist at BMW in South Carolina, USA. She works within their innovation and research group to develop technology for the BMW Group. In addition to this role, she works as a graduate coach helping others navigate the tricky grad school world. Her goals are to bring more diverse voices to academia and tech.
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.
Get one step further in advanced analytics with a short overview of 4 features in DSS: Data exploration, data preparation, Analytics automation and a bit of AutoML, all in 30 minutes, with in-depth demo in our solution DSS.
It's no secret that Excel poses massive limitations for organizations as they look to most effectively utilize data, with its lack of functions for size and volume, auditability, and automated workflows. In this session, we'll provide you with a solution to bypass the frustration. Enter Dataiku as an alternative, and learn how to work on big data as easily as small data. In this session, our financial services expert and solutions engineer, Will Nowak, will address this key challenge through use cases, notable examples, and industry observations from our customers in the space.
2:00pm: Intro
2:05pm: Data Science in Compliance and Fraud Detection w/ Spotify
2:45pm: Q&A
Talk Abstract:
Data Science is an emerging function in a variety of industries and a greater number of data scientists have begun working on personalization, recommendations, or sales optimizations.
The cost of compliance has also been expanding in most industries and especially in the technology sector. This is a result of the Public’s attention shift from traditional frauds to antitrust, conflict of interest, and data privacy. While there are plenty of opportunities to leveraging DS/ML to solve such problems, the complex nature of such compliance and fraud detection issues stymies data practitioners from being able to grow the data science practice. The “language barrier” of communication between the company’s DS/business/compliance appears to hide the low hanging fruits.
In this talk, Harry will share his experience in connecting data science with compliance, examples of the DS/ML use cases, and key takeaways for our two groups of the audience (Data Scientists and Business Stakeholders.)
• Hidden Data Science Opportunity in Compliance and Finance
• Career Journey: from a fraud investigator to a data scientist
• Opportunities that often get overlooked in compliance/fraud functions
• How to speak two languages: recommendations on connecting data science resources with compliance business
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.
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 into timely insights via predictive maintenance with automated insight improvement.
During this webinar, we will:
- Determine when purchased equipment might fail to deploy resources to service customers
- Look at root cause analysis and model drift.
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.
Using NLP to Find the Internet’s Favorite RecipesKatie Gross, Lead Data Scientist @ Dataiku[[ webcastStartDate * 1000 | amDateFormat: 'MMM D YYYY h:mm a' ]]27 mins