podcast

  • Founder Interview – Francesco Gadaleta of Fitchain

    Cross-posting from Cryptoradio.io Overview Francesco Gadaleta introduces Fitchain, a decentralized machine learning platform that combines blockchain technology and AI to solve the data manipulation problem in restrictive environments such as healthcare ...

  • Episode 31: The End of Privacy

    Data is a complex topic, not only related to machine learning algorithms, but also and especially to privacy and security of individuals, the same individuals who create such data just by using the many mobile apps and services that characterize their di...

  • Episode 30: Neural networks and genetic evolution: an unfeasible approach

    Despite what researchers claim about genetic evolution, in this episode we give a realistic view of the field.

  • Episode 29: Fail your AI company in 9 steps

    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.

  • Episode 28: Towards Artificial General Intelligence: preliminary talk

    The enthusiasm for artificial intelligence is raising some concerns especially with respect to some ventured conclusions about what AI can really do and what its direct descendent, artificial general intelligence would be capable of doing in the immediat...

  • Episode 27: Techstars accelerator and the culture of fireflies

    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-s...

  • Episode 26: Deep Learning and Alzheimer

    In this episode I speak about Deep Learning technology applied to Alzheimer disorder prediction. I had a great chat with Saman Sarraf, machine learning engineer at Konica Minolta, former lab manager at the Rotman Research Institute at Baycrest, Universit...

  • Episode 25: How to become data scientist [RB]

    In this episode, I speak about the requirements and the skills to become data scientist and join an amazing community that is changing the world with data analyticsa

  • Episode 24: How to handle imbalanced datasets

    In machine learning and data science in general it is very common to deal at some point with imbalanced datasets and class distributions. This is the typical case where the number of observations that belong to one class is significantly lower than those...

  • Episode 23: Why do ensemble methods work?

    Ensemble methods have been designed to improve the performance of the single model, when the single model is not very accurate. According to the general definition of ensembling, it consists in building a number of single classifiers and then combining o...

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