Archive for the 'startups' Category

In this episode I have a chat with Sandeep Pandya, CEO at Everguard.ai a company that uses sensor fusion, computer vision and more to provide safer working environments to workers in heavy industry.
Sandeep is a senior executive who can hide the complexity of the topic with great talent.

 

This episode is supported by Pryml.io
Pryml is an enterprise-scale platform to synthesise data and deploy applications built on that data back to a production environment.
Test ideas. Launch new products. Fast. Secure.

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There are very good reasons why a financial institution should never share their data. Actually, they should never even move their data. Ever.
In this episode I explain you why.

 

 

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Building reproducible models is essential for all those scenarios in which the lead developer is collaborating with other team members. Reproducibility in machine learning shall not be an art, rather it should be achieved via a methodical approach. 
In this episode I give a few suggestions about how to make your ML models reproducible and keep your workflow as smooth.

Enjoy the show!

Come visit us on our discord channel and have a chat

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Data science and data engineering are usually two different departments in organisations. Bridging the gap between the two is essential to success. Many times the brilliant applications created by data scientists don't find a match in production, just because they are not production-ready.

In this episode I have a talk with Daan Gerits, co-founder and CTO at Pryml.io

 

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Scaling technology and business processes are not equal. Since the beginning of the enterprise technology, scaling software has been a difficult task to get right inside large organisations. When it comes to Artificial Intelligence and Machine Learning, it becomes vastly more complicated. 

In this episode I propose a framework - in five pillars - for the business side of artificial intelligence.

 

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The two most widely considered software development models in modern project management are, without any doubt, the Waterfall Methodology and the Agile Methodology. In this episode I make a comparison between the two and explain what I believe is the best choice for your machine learning project.

An interesting post to read (mentioned in the episode) is How businesses can scale Artificial Intelligence & Machine Learning https://amethix.com/how-businesses-can-scale-artificial-intelligence-machine-learning/

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In this episode I have a wonderful conversation with Chris Skinner.

Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker - that’s how he defines himself - saying that “People are not educated with loans, credit, money” and that “Banks are failing at digital”.

After I got my hands on his last book Digital Human, I invited him to the show to ask him a few questions about innovation, regulation and technology in finance.

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In this episode I have a wonderful conversation with Chris Skinner.

Chris and I recently got in touch at The banking scene 2019, fintech conference recently held in Brussels. During that conference he talked as a real trouble maker - that’s how he defines himself - saying that “People are not educated with loans, credit, money” and that “Banks are failing at digital”.

After I got my hands on his last book Digital Human, I invited him to the show to ask him a few questions about innovation, regulation and technology in finance.

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In order to succeed with artificial intelligence, it is better to know how to fail first. It is easier than you think.
Here are 9 easy steps to fail your AI startup.

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In the aftermath of the Barclays Accelerator, powered by Techstars experience, one of the most innovative and influential startup accelerators in the world, I’d like to give back to the community lessons learned, including the need for confidence, soft-skills, and efficiency, to be applied to startups that deal with artificial intelligence and data science.
In this episode I also share some thoughts about the culture of fireflies in modern and dynamic organisations.

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