Operationalizing Your Machine Learning Solutions:

Strategies for Success

The past few years have seen organizations have to cope with disruption on a global scale, with business resilience being tested like never before. As noted in our Digital Resilience Pays Off report, being able to prepare for change was a key factor in building resilience to thrive through uncertain times.

One subject that is often close to change and innovation is Machine Learning (ML). With estimates suggesting that 87% of data science projects fail to make it to production, however, how can you successfully leverage innovative technologies? Join us to learn about how Splunk is approaching data science and machine learning to help you harness the power of your data.

During this session, we will discuss:

  • How use of AI and ML can increase your insights, efficiency and ultimately resilience
  • Some of the key challenges operationalizing ML in production systems
  • How to use new features in the Machine Learning Toolkit (MLTK) to deploy pre-trained models in Splunk
  • How MLTK and the Splunk App for Data Science and Deep Learning work better together

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Time Place Details
10:00am - 10:55am Expo Hall Meet and greet in the lobby outside the Expo Hall before the General Assembly.
11:00am - 11:55am Rm 314 Expert Track: TOP 10 WAYS TO MAKE A DIFFERENCE IN THE INDUSTRY | John Dough, CFO Marketizingly
11:00am - 11:55am Rm 159 Social Track: MODERN NETWORKING | Hosted by: SponsorName

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Our Speakers

Poonam Yadav

Senior Product Manager Machine Learning
Splunk Inc.

Poonam Yadav combines her deep technical background with a passion for building great products. She is a Product Manager for Machine Learning at Splunk. In this role, Poonam works on defining the strategy and roadmap for the machine learning area at Splunk and is responsible for executing on that strategy. Previously, Poonam was a Product Manager in the application security domain. She led Micro Focus Fortify's flagship product, a static application security product to find vulnerabilities in application source code. Poonam received a MBA degree from Cornell University, Master of Science in Microelectronics from Indian Institute of Technology Bombay and Bachelor of Science in Electronics Engineering from Mumbai University.

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Greg Ainslie-Malik

Principal Strategic Advisor
Splunk Inc.

Greg is a recovering mathematician and part of the technical advisory team at Splunk, specializing in how to get value from machine learning and advanced analytics. Previously the product manager for Splunk’s Machine Learning Toolkit (MLTK) he helped set the strategy for machine learning in the core Splunk platform. A particular career highlight was partnering with the World Economic Forum to provide subject matter expertise on the AI Procurement in a Box project.
Before working at Splunk he spent a number of years with Deloitte and prior to that BAE Systems Detica working as a data scientist. Ahead of getting a proper job he spent way too long at university collecting degrees in math including a PhD on “Mathematical Analysis of PWM Processes”.
When he is not at work he is usually herding his three young lads around while thinking that work is significantly more relaxing than being at home

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Philipp Drieger

Global Principal Machine Learning Architect
Splunk Inc.

Philipp Drieger works as a Global Principal Machine Learning Architect at Splunk. He accompanies Splunk customers and partners across various industries in their digital journeys, helping to achieve advanced analytics use cases in cybersecurity, IT operations, IoT and business analytics. Before joining Splunk, Philipp worked as freelance software developer and consultant focusing on high performance 3D graphics and visual computing technologies. In research, he has published papers on text mining and semantic network analysis.

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