Recent Posts

• September 26, 2020podcast

  Why synthetic data cannot boost machine learning (Ep. 120)

  Come join me in our Discord channel speaking about all things data science. Follow me on Twitch during my live coding sessions usually in Rust and Python This episode is […]

• 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...