Oguzhan Gencoglu's guest appearances

Oguzhan Gencoglu

Analytics and Data Science Pulse

How AI Built This

MLOps.community 

Driven by Data: The Podcast

Calum Chace

Rob Walker

Jeremy Howard

Andrew Jones

Daniel Jeffries

Peter Jackson

Byron Allen

Scott Taylor

Ryan Dawson

Joel Grus

Helen Brown

Burton Snowboards

Matthew Rocklin

Maxime Beauchemin

Daniel Stahl

OwlTail

MLOps community meetup #62! Last Wednesday we talked to Oguzhan Gencoglu, Co-founder &amp; Head of AI, Top Data Science.  //Abstract Starting the AI adoption with AI Proof-of-Concepts (PoCs) is the most common choice for most companies. Yet, a significant percentage of AI PoCs do not make it into production whether they were successful or not. Furthermore, running yet another AI PoC follows the law of diminishing returns in various aspects. This talk will revolve around this theme.  //Bio Oguzhan "Ouz" Gencoglu is the Co-founder and Head of AI at Top Data Science, a Helsinki-based AI consultancy. With his team, he delivered more than 70 machine learning solutions in numerous industries for the past 5 years. Before that, he used to conduct machine learning research in several countries including the USA, Czech Republic, Turkey, Denmark, and Finland. Oguzhan has given more than 40 talks on machine learning to audiences of various backgrounds.  ----------- Connect With Us ✌️-------------    Join our Slack community:  https://go.mlops.community/slack Follow us on Twitter:  @mlopscommunity Sign up for the next meetup:  https://go.mlops.community/register  Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Oguzhan on LinkedIn: https://www.linkedin.com/in/ogencoglu/  Timestamps: [00:00] Introduction to Oguzhan Gencoglu [00:47] Ouz's background [01:47] Recurring/repetitive problem patterns [03:16] "When you solve a repetitive task in an automatic way, that's Scalability." [04:32] Evolution expected of Machine Learning [05:10] "People are quite confused about the titles and what's worst, those titles don't have a common definition in different companies. If you feel a little bit overwhelmed, that's normal." [08:04] Proof-of-Concepts [10:35] Successful PoCs but not Productionized [16:03] Productionize as soon as possible [16:47] "In your Proof-of-Concepts, it's not only technical, but it's also a mindset." [20:00] Framework of a successful PoCs [24:28] Taking too much on PoCs [28:05] Proof-of-Concepts after Proof-of-Concepts and Proof-of-Concepts hell [31:30] Wholistic view [34:00] Operationalizing PoCs [37:17] "The teams also need to adjust themselves to these new tools, new paradigms, and the different needs of the whole industry."   [37:26] Horror stories [39:54] Open communication tips 43:31] "Open communication should not only be from the technical perspective but also down to the business and strategy perspective." [44:20] Translation tips [44:39] "I believe the most crucial part of today's ML scientists' role is not building a machine learning model but translating a real-life problem into a machine learning problem. It's crucial because it's a scarce talent and skill." [49:30] Realistic budget for small PoCs [50:18] "You need at least 1 month of work of proof of value but that doesn't mean things will go to production." [51:40] Understanding the questions fully [52:55] "That translation skill is the greatest skill to have in this industry because you can't auto ML that or whatever. It stands the test of time because that will be needed all the time." 

MLOps community meetup #62! Last Wednesday we talked to Oguzhan Gencoglu, Co-founder &amp; Head of AI, Top Data Science. //Abstract Starting the AI adoption with AI Proof-of-Concepts (PoCs) is the most common choice for most companies. Yet, a significant percentage of AI PoCs do not make it into production whether they were successful or not. Furthermore, running yet another AI PoC follows the law of diminishing returns in various aspects. This talk will revolve around this theme. //Bio Oguzhan "Ouz" Gencoglu is the Co-founder and Head of AI at Top Data Science, a Helsinki-based AI consultancy. With his team, he delivered more than 70 machine learning solutions in numerous industries for the past 5 years. Before that, he used to conduct machine learning research in several countries including the USA, Czech Republic, Turkey, Denmark, and Finland. Oguzhan has given more than 40 talks on machine learning to audiences of various backgrounds. ----------- Connect With Us ✌️-------------    Join our Slack community:  https://go.mlops.community/slack Follow us on Twitter:  @mlopscommunity Sign up for the next meetup:  https://go.mlops.community/register Connect with Demetrios on LinkedIn: <a href="https://www.linkedin.com/in/dpbrinkm/" rel="nofollow" target="_blank">https://www.linkedin.com/in/dpbrinkm/</a> Connect with Oguzhan on LinkedIn: <a href="https://www.linkedin.com/in/ogencoglu/" rel="nofollow" target="_blank">https://www.linkedin.com/in/ogencoglu/</a> Timestamps: [00:00] Introduction to Oguzhan Gencoglu [00:47] Ouz's background [01:47] Recurring/repetitive problem patterns [03:16] "When you solve a repetitive task in an automatic way, that's Scalability." [04:32] Evolution expected of Machine Learning [05:10] "People are quite confused about the titles and what's worst, those titles don't have a common definition in different companies. If you feel a little bit overwhelmed, that's normal." [08:04] Proof-of-Concepts [10:35] Successful PoCs but not Productionized [16:03] Productionize as soon as possible [16:47] "In your Proof-of-Concepts, it's not only technical, but it's also a mindset." [20:00] Framework of a successful PoCs [24:28] Taking too much on PoCs [28:05] Proof-of-Concepts after Proof-of-Concepts and Proof-of-Concepts hell [31:30] Wholistic view [34:00] Operationalizing PoCs [37:17] "The teams also need to adjust themselves to these new tools, new paradigms, and the different needs of the whole industry."   [37:26] Horror stories [39:54] Open communication tips 43:31] "Open communication should not only be from the technical perspective but also down to the business and strategy perspective." [44:20] Translation tips [44:39] "I believe the most crucial part of today's ML scientists' role is not building a machine learning model but translating a real-life problem into a machine learning problem. It's crucial because it's a scarce talent and skill." [49:30] Realistic budget for small PoCs [50:18] "You need at least 1 month of work of proof of value but that doesn't mean things will go to production." [51:40] Understanding the questions fully [52:55] "That translation skill is the greatest skill to have in this industry because you can't auto ML that or whatever. It stands the test of time because that will be needed all the time."

Law of Diminishing Returns for Running AI Proof-of-Concepts // Oguzhan Gencoglu // MLOps Meetup #62

In Episode 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Oguzhan Gencoglu, Head of AI at Top Data Science, (a Data Science Consultancy that is ranked as one of the best Artificial Intelligence consultancies in Finland) where they talk about how to go beyond the proof of concept cycle with Artificial Intelligence.  Oguzhan has given over 40 "talks" on the subject of AI, has numerous publications and has delivered over 60 AI solutions into production, and he shared the key considerations of productionising AI, which includes:How FOMO is a driver behind many AI projectsThe importance of how data is collected How to check the pulse of commitment within the businessWhy "top down" commitment is key How the cost implications are more than just the implementation costWhy POC failure is a good thing How to build a production level solution even in a disparate environmentWhy most POC's are successful but rarely make it to production Why you need more than just Data Scientists &amp; ML EngineersHow mindset and culture determine success

In Episode 7 of Driven by Data: The Podcast, Kyle Winterbottom is joined by Oguzhan Gencoglu, Head of AI at Top Data Science, (a Data Science Consultancy that is ranked as one of the best Artificial Intelligence consultancies in Finland) where they talk about how to go beyond the proof of concept cycle with Artificial Intelligence. Oguzhan has given over 40 "talks" on the subject of AI, has numerous publications and has delivered over 60 AI solutions into production, and he shared the key considerations of productionising AI, which includes:<ul><li>How FOMO is a driver behind many AI projects</li><li>The importance of how data is collected </li><li>How to check the pulse of commitment within the business</li><li>Why "top down" commitment is key </li><li>How the cost implications are more than just the implementation cost</li><li>Why POC failure is a good thing </li><li>How to build a production level solution even in a disparate environment</li><li>Why most POC's are successful but rarely make it to production </li><li>Why you need more than just Data Scientists &amp; ML Engineers</li><li>How mindset and culture determine success</li></ul>

Ep 7 | Going Beyond Proof of Concept in AI with Oguzhan Gencoglu, Founder & Head of AI at Top Data Science

In episode 12, I was joined by Oguzhan Gencoglu of Top Data Science in Helsinki. Top Data Science is a data science company focusing on AI powered Computer Vision, Machine Learning and Analytics technologies and development services for corporate customers and tech companies. Oguzhan has a Masters in Machine Learning from Tampere University and to date, he has delivered over 50+ AI projects in the past 3 and a half years with Top Data Science. Thanks for taking part Oguzhan.

Analytics and Data Science Pulse - #012. Q&A with Oguzhan Gencoglu of Top Data Science