28 min

Damien Benveniste PhD - Machine Learning 101 Redefining AI - Artificial Intelligence with Squirro

    • Technology

In this episode Lauren Hawker Zafer is joined by Damien Benveniste PhD⁠ 

Who is Damien Benveniste PhD?

10 years ago, after a Ph.D. in theoretical Physics, Damien started his career in Machine Learning and Data Science.

He has been a Data Scientist, Machine Learning Engineer, and a Software Engineer. In these roles he has led various machine learning projects in diverse industry sectors such as: AdTech, Market Research, Financial Advising, Cloud Management, Online Retail, Marketing, Credit Score Modeling, Data Storage, Healthcare and Energy Valuation. 

Recently, he was a machine learning tech lead at Meta on the automation at scale of model optimisation for Ads ranking. He is also a machine learning top voice on LinkedIn.

At present, Damien focuses on a more entrepreneurial journey where he builds tech businesses and writes about his experience. If you are interested in reading about his experience then check out his newsletter: ⁠The AI Edge.⁠



Why this Episode?

🎙️ Get ready to embark on an enlightening journey through the world of Machine Learning 101! 🤖

In our upcoming episode, we're diving deep into the fundamental concepts of machine learning and navigating the complexities of this ever-evolving field. 



Join us as Lauren and Damien explore:

🤔 What confuses people when discussing machine learning, and how can we untangle the web of differences in learning?

🌟 Discover the essential distinctions between supervised, unsupervised, and reinforcement learning, and see how they tackle real-world problems head-on.

🧠 Uncover the secrets of neural networks and explore the magic of CNNs and RNNs in solving diverse problems.

📸 Delve into the world of unstructured data, from images to text and audio, and uncover the challenges and considerations in ML tasks.

📊 Learn how to handpick and evaluate the perfect performance metrics for various machine learning tasks.

🤯 Delve into the trade-offs between model complexity and interpretability, with a spotlight on model explainability in real-world applications.

💡 Explore the ethical considerations and potential risks of deploying machine learning models, and discover how to ensure responsible AI development.

🤖 As well as: can Machines Learn Morality? Dive into the exciting world of ethical reasoning in AI, and uncover the challenges and opportunities that lie ahead.

Don't miss this episode where we unravel the fascinating world of Machine Learning 101! Tune in for a journey of knowledge and insight into the heart of artificial intelligence. 🚀 #RedefiningAI #MachineLearning101 



REDEFINING AI is powered by The Squirro Academy - learn.squirro.com. Try our free courses on AI, ML, NLP and Cognitive Search at the Squirro Academy and find out more about Squirro here.

In this episode Lauren Hawker Zafer is joined by Damien Benveniste PhD⁠ 

Who is Damien Benveniste PhD?

10 years ago, after a Ph.D. in theoretical Physics, Damien started his career in Machine Learning and Data Science.

He has been a Data Scientist, Machine Learning Engineer, and a Software Engineer. In these roles he has led various machine learning projects in diverse industry sectors such as: AdTech, Market Research, Financial Advising, Cloud Management, Online Retail, Marketing, Credit Score Modeling, Data Storage, Healthcare and Energy Valuation. 

Recently, he was a machine learning tech lead at Meta on the automation at scale of model optimisation for Ads ranking. He is also a machine learning top voice on LinkedIn.

At present, Damien focuses on a more entrepreneurial journey where he builds tech businesses and writes about his experience. If you are interested in reading about his experience then check out his newsletter: ⁠The AI Edge.⁠



Why this Episode?

🎙️ Get ready to embark on an enlightening journey through the world of Machine Learning 101! 🤖

In our upcoming episode, we're diving deep into the fundamental concepts of machine learning and navigating the complexities of this ever-evolving field. 



Join us as Lauren and Damien explore:

🤔 What confuses people when discussing machine learning, and how can we untangle the web of differences in learning?

🌟 Discover the essential distinctions between supervised, unsupervised, and reinforcement learning, and see how they tackle real-world problems head-on.

🧠 Uncover the secrets of neural networks and explore the magic of CNNs and RNNs in solving diverse problems.

📸 Delve into the world of unstructured data, from images to text and audio, and uncover the challenges and considerations in ML tasks.

📊 Learn how to handpick and evaluate the perfect performance metrics for various machine learning tasks.

🤯 Delve into the trade-offs between model complexity and interpretability, with a spotlight on model explainability in real-world applications.

💡 Explore the ethical considerations and potential risks of deploying machine learning models, and discover how to ensure responsible AI development.

🤖 As well as: can Machines Learn Morality? Dive into the exciting world of ethical reasoning in AI, and uncover the challenges and opportunities that lie ahead.

Don't miss this episode where we unravel the fascinating world of Machine Learning 101! Tune in for a journey of knowledge and insight into the heart of artificial intelligence. 🚀 #RedefiningAI #MachineLearning101 



REDEFINING AI is powered by The Squirro Academy - learn.squirro.com. Try our free courses on AI, ML, NLP and Cognitive Search at the Squirro Academy and find out more about Squirro here.

28 min

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