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• September 16, 2020podcast

  Machine learning in production: best practices [LIVE from twitch.tv]

  Hey there! Having the best time of my life 😉 This is the first episode I record while I am live on my new Twitch channel 🙂 So much fun! […]

• September 4, 2020podcast

  Testing in machine learning: checking deep learning models (Ep. 118)

  In this episode I speak with Adam Leon Smith, CTO at DragonFly and expert in testing strategies for software and machine learning.We cover testing with deep learning (neuron coverage, threshold […]

• August 29, 2020podcast

  Testing in machine learning: generating tests and data (Ep. 117)

  In this episode I speak with Adam Leon Smith, CTO at DragonFly and expert in testing strategies for software and machine learning. On September 15th there will be a live@Manning […]

• August 12, 2020podcast

  Why you care about homomorphic encryption (Ep. 116)

  After deep learning, a new entry is about ready to go on stage. The usual journalists are warming up their keyboards for blogs, news feeds, tweets, in one word, hype.This […]

• August 3, 2020podcast

  Test-First machine learning (Ep. 115)

  In this episode I speak about a testing methodology for machine learning models that are supposed to be integrated in production environments. Don’t forget to come chat with us in […]

• July 26, 2020podcast

  GPT-3 cannot code (and never will) (Ep. 114)

  The hype around GPT-3 is alarming and gives and provides us with the awful picture of people misunderstanding artificial intelligence. In response to some comments that claim GPT-3 will take […]

• July 22, 2020podcast

  Make Stochastic Gradient Descent Fast Again (Ep. 113)

  There is definitely room for improvement in the family of algorithms of stochastic gradient descent. In this episode I explain a relatively simple method that has shown to improve on […]

• July 20, 2020podcast

  What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)

  In this episode I speak about data transformation frameworks available for the data scientist who writes Python code.The usual suspect is clearly Pandas, as the most widely used library and […]

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  July 5, 2020podcast

  [RB] It’s cold outside. Let’s speak about AI winter (Ep. 111)

  In this episode I speak with Filip Piekniewski about some of the most worth noting findings in AI and machine learning in 2019. As a matter of fact, the entire field of AI has been inflated by hype and claims that are hard to believe. A lot of the promis...

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  June 29, 2020podcast

  Rust and machine learning #4: practical tools (Ep. 110)

  In this episode I make a non exhaustive list of machine learning tools and frameworks, written in Rust. Not all of them are mature enough for production environments. I believe that community effort can change this very quickly. To make a comparison with...