How Can You Transform Machine Learning Programs for Value?

Key takeaways

Many organisations invest heavily in machine learning but see little return due to misaligned priorities and unclear business objectives.

Transforming data science from a research-focused effort into a core business function is essential for realising its value.

Establishing a robust information architecture is crucial for effective machine learning integration within an organisation.

Insights from IBM's extensive AI engagements can guide companies in optimising their machine learning programmes.

Many companies have been sold on the promise of artificial intelligence. They modeled their expectations after their favourite digital-born companies. They have piled a ton of money into hiring expensive data scientists and ML engineers. They invested heavily in software and hardware. They spend considerable time ideating. Yet despite all this effort and money, many of these companies are enjoying little to no meaningful benefit. This is primarily because they have spent all these resources on too much experimentation, projects with no clear business purpose, and activity that doesn’t align with organizational priorities. To turn data science from a scam to source of value, enterprises need to consider turning their data science programs from research endeavor’s into integral parts of their business and processes. At the same time, they need to consider laying down a true information architecture foundation. Listen to Prasanna Keny and Nishant Arora, as they share learnings & best practices from IBM's 16000 AI engagements.

Speaker profiles –

Prasanna Keny - Sr Technology Manager - IBM Analytics
Nishant Arora - Analytics Marketing Leader- IBM Asia Pacific

Date: 03rd August 2018 Time: 03 PM to 04 PM, IST

IBM Cloud - Don't let machine learning become a scam - Transform your organisation’s machine learning programs from a scam to a source of value | Join this Webinar

Key takeaways

Speaker profiles –

Register for this webinar to understand how you can accelerate your enterprise’s machine learning adoption at scale.

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