Eric Siegel
@predictanalytic
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Founder of Machine Learning Week, author of "The AI Playbook" and the best-seller "Predictive Analytics," former Columbia U. professor, and Forbes contributor.
SF Bay Area
Joined May 2009
Shouldn’t a great model be a sure bet to deploy? The answer is no. Check out this recap of my AI Realized keynote: https://t.co/BXHCutCi0v
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AI is on the cusp of greatness. Positive returns are still few and far between – but the final mile to more universally realized value is in sight. Let's get there together. Come to: ML Week’s HYBRID AI 2026 (May 5-6) https://t.co/eYx6nRABXD
#MLweek
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Here's the new frontier for #predictiveAI: a new kind of ML software for planning, selling, & greenlighting #MLmodel deployment. There's nothing like trying it out yourself. Participate in this popular hands-on @DataCamp webinar – now available on demand. https://t.co/zp2pbAZld8
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You can now view, on demand, the @IBM Z Day presentation that I gave last week: "Seven Ways to Hybridize Predictive and Generative AI" https://t.co/DyjE1pX2GJ
#ibmzday
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#PredictiveAI routinely fails to deploy, so #datascientists are spearheading a movement to focus on its #businessvalue. My latest in @Forbes covers 4 common concerns about #MLvaluation and how to address them
forbes.com
Predictive AI routinely fails to deploy, so data scientists are spearheading a movement to focus on its business value. But stakeholders need a better understanding.
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It was a pleasure appearing on "Bringing Data and AI to Life"! Nick is a great host and navigated an expansive discussion of #predictiveAI, #genAI, and how to realize a measurable impact.
Data’s only useful if it’s coherent and pulled together. Tune into the latest episode of Bringing Data and AI To Life as industry expert Eric Siegel shares the secrets behind quality data. Tune in: https://t.co/f5AZ1WOCDk
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#GenAI is super advanced – but it doesn’t replace #predictiveAI, it only augments it. The two will remain intrinsically distinct, even as they’re strategically married. My latests in @Forbes explains why: https://t.co/YCjWC9jK97
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I'm excited to present at @IBM Z Day 2025 – a free online event on November 12! I'll be presenting on: "Seven Ways to Hybridize Predictive and Generative AI" Overall, IBM Z Day has 6 content-rich technical tracks. https://t.co/DyjE1pX2GJ
#ibmzday
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It was a pleasure appearing on The AI Space Podcast!
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Join us in congratulating, @predictanalytic, author of The AI Playbook: Mastering the Rare Art of Machine Learning Deployment! Eric Siegel has crafted a powerful guide for anyone serious about putting machine learning into action! 🏆 📚 #APEXAwards #PublishingAwards
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𝗖𝗮𝗹𝗹 𝗳𝗼𝗿 𝘀𝗽𝗲𝗮𝗸𝗲𝗿𝘀 𝗮𝗻𝗱 𝘀𝗮𝘃𝗲-𝘁𝗵𝗲-𝗱𝗮𝘁𝗲: In 2026, Machine Learning Week will return to SF as: 𝗛𝗬𝗕𝗥𝗜𝗗 𝗔𝗜 𝟮𝟬𝟮𝟲 – May 5-6 in San Francisco 𝗛𝘆𝗯𝗿𝗶𝗱 𝗔𝗜 is vital for turning AI’s potential into realized value. https://t.co/AJIKr4G3h3
machinelearningweek.com
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#GenerativeAI and #predictiveAI need one another. They're destined to marry because each is suited to address the other's greatest limitations. Read my latest @Forbes article to see how this works:
forbes.com
Generative and predictive AI need one another. They're destined to marry because each is suited to address the other's greatest limitations. Here are two ways.
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I'm excited to participate at @Twilio's Transform Together in NYC on November 4! I'll be interviewed in a fireside chat on the realities of implementing #AI at enterprise scale. Hope to see you there! https://t.co/U9CvkylJDz
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The most ideal way to soften the #AIbubble’s looming explosion would be to boost #AI’s realized value. How? A new #reliabilitylayer that tames #largelanguagemodels. Read my latest in @Forbes: https://t.co/miVDZONKGB
#genAI #LLMs
forbes.com
The most ideal way to soften the AI bubble’s looming explosion would be to boost AI’s realized value. How? A new reliability layer that tames large language models.
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5 seconds from now, you could be trying https://t.co/myym0oLz9L hands on, interactively maximizing the value of #machinelearning deployment. With one click, jump into any of 7 projects – #frauddetection, marketing, #creditscoring, #churn, #healthcare, etc
gooder.ai
Try your hand at interactively maximizing the value of ML deployment, across a range of predictive AI projects.
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❣ https://t.co/1wKv73p6jH by @predictanalytic The #AI Playbook offers invaluable insights & practical steps for successful #MachineLearning deployments, proposing bizML as a more current, pertinent, & compelling industry-standard methodology than CRISP-DM.
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I'm excited to participate at @twilio's Transform Together in Seattle on October 7! I'll be interviewed in a fireside chat on the realities of implementing AI at enterprise scale. Hope to see you there!
twilio.com
Create amazing customer experiences with our Customer Engagement Platform (CEP) that combines communication APIs with AI. Build solutions for SMS, WhatsApp, voice, and email.
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Gooder AI has launched its professional services. Stop letting great #models gather dust. Let's work together to maximize the operationalized value of #predictiveAI – and create compelling biz cases that get your ML projects deployed & delivering value
gooder.ai
Stop letting great models gather dust. Engage the Gooder AI team to maximize the operationalized value of predictive AI – and to create compelling business cases that get your machine learning...
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We need to unf*ck ML. #PredictiveAI offers tremendous potential – but it has a notoriously poor track record. Most initiatives fail to deploy, never realizing value. #GooderAI empowers stakeholders & #datascientists to plan, sell & greenlight deployment.
gooder.ai
Gooder AI empowers stakeholders and data scientists alike to plan, sell, and greenlight predictive AI deployment. It establishes and maximizes the value of each machine learning model in terms of...
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#Datascientists consider #businessmetrics more important than technical #metrics – yet in practice they focus more on technical ones. This derails most #predictiveAI projects. So, why? Check out my latest in @Forbes
forbes.com
Data scientists consider business metrics more important than technical metrics – yet in practice they focus more on technical ones. This derails most projects. So, why?
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