Everyday AI Conference by Dataiku

Despite the hype across tech around data science, it is currently estimated that 80% of machine learning projects fail. There are some large and glaring reasons that this is the case... here are the biggest.

Principles for the development of fair machine learning systems are now widespread, however, what a development team actually has to do to get things moving is often still unclear.

This session will dive into some of the practical considerations surrounding the application of fairness, to give attendees more understanding of what their companies might do to move the needle on this topic. The practical application of fairness is a key component in moving the conversation forward around how we can use trustworthy AI to reduce reputational & compliance risk.

Key takeaways:
- What is ML fairness and where does unfair bias enter into ML driven systems?
- What are the headwinds that a development team faces in the application of fairness?
- What approaches are available for structuring a fairness solution?

[From the Everyday AI Conference] Why are events in the data industry dominated by a minority population?
One reason is history, another is that change is slow, and neither is acceptable.
Hear from Eva Murray, Lead EMEA Evangelist at Snowflake on this topic.

Over the past five years, there has been massive growth within retailers looking to use machine learning and AI to improve performance, simplify the customer journey and increase innovation.
But should we always trust the algorithms, and are they even required?

Before data science was in vogue, the humble actuary was one of the original careers using data analytics to drive key functions within insurance and pensions.

Get an introduction of what an actuary does with an insurance company, the challenges they face, and how the profession is evolving in the new world.

[From the Everyday AI Conference]

Nothing and no one works in a vacuum.
Data engineers, data scientists, and business analysts all need to work together to complete a project. But that’s often not the way it goes. Silos prevent us from working as a cohesive team.

Utilizing your entire Data Stack, from cloud storage (AWS, Snowflake) to data preparation (Dataiku) and visualization (Tableau, PowerBI), is key to creating a collaborative experience.

GE is a world leader in the manufacture of commercial jet engines, offering products for many of the best-selling commercial airframes.

GE Aviation has over a hundred Data Scientists using Dataiku to develop analytics and drive insights. In this talk we will share some of the ways we have been using Dataiku to solve our problems and share the successes and lessons learned along the way.

From Reyjaïvik to Jeddah, EMEA is facing various maturity levels when it comes to AI.
This video unveils the path toward AI that Dataiku envisions for the region.

The session will cover how different clients are adopting ML Ops capability for scaling their data science models.

The key focus of this session will be to share Deloitte’s thinking adapting to the new ML Ops capability and the impact on the operating model for various organisations.

The Luxoft Analytics team has delivered many Dataiku-based solutions, both internally and externally.

In this presentation, we discuss key success factors for commercially successful implementations and roll-outs.

Knowing that 97% of the floating plastic entering the oceans ends-up onshore, various organizations are focusing on beach areas to conduct cleanup activities.
Dataikers and The Ocean Cleanup modelers have collaborated to collect data from over 15 organizations and build the world’s largest beach cleanup database.

Companies rarely are at a loss for ideas about AI use cases that could improve their business - but having the technical resources or know-how to tackle these problems is a different story.

Dataiku's Industry Solutions are off-the-shelf, starter projects and assets that are designed to help solve vertical-specific challenges.

How do we elevate people to make better decisions with data?
Beyond the tagline, learn it firsthand from Craig Turrell, Head of Digital & Business Science, Finance Operations at Standard Chartered Bank, who will share his award-winning story.

Different financial services organisations, including UBS, First International Bank of Israel (FIBI), and ACI Worldwide share their journey to Everyday AI.