Data Science at Home

Data Science at Home

By Francesco GadaletaNewsTechnologyTech News
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Data Science at Home episodes

  • Reinforcement Learning is all you need. Or is it? (Ep. 165)

    Is reinforcement learning sufficient to build truly intelligent machines? Listen to this episode to find out.

    Our Sponsors

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    Amethix Technologies

    Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

     

     

    References
    • https://bdtechtalks.com/2021/06/07/deepmind-artificial-intelligence-reward-maximization/
  • https://pub.towardsai.net/building-reinforcement-learning-agents-that-learn-to-collaborate-and-compete-at-the-same-time-d081fea942d2
  • https://towardsdatascience.com/intro-to-reinforcement-learning-temporal-difference-learning-sarsa-vs-q-learning-8b4184bb4978
  •  

    31 min
  • What's happening with AI today? (Ep. 164)
    In this episode I have a wonderful chat with Ronald Schmelzer and Kathleen Walch, authors of "AI Today" the top podcast for those wanting a no-hype, practical, real-world insight into what enterprises, public sector agencies, thought leaders, leading technology companies, pundits, and experts are doing with AI today.
     
     
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    Sponsored by Amethix Technologies

    Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

     

     
    Links
     
    • AI Today podcast: http://aitoday.live/
  • CPMAI Methodology: https://www.cognilytica.com/cpmai-methodology/
  • 26 min
  • 2 effective ways to explain your predictions (Ep. 163)

    Our Sponsor

    Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

     

     

    References

    Fisher, Aaron, Cynthia Rudin, and Francesca Dominici. “Model Class Reliance: Variable importance measures for any machine learning model class, from the ‘Rashomon’ perspective.” http://arxiv.org/abs/1801.01489 (2018).

  • Python SHAP
  • https://github.com/slundberg/shap

     

     

    25 min
  • The Netflix challenge. Fair or what? (Ep. 162)

    Remember the Netflix challenge?

    It was a ton of money for the one who would have cracked the problem of recommending the best possible movie.

    Was it a fair challenge? Did it work?

    Let me tell you what happened...

     

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    22 min
  • Artificial Intelligence for Blockchains with Jonathan Ward CTO of Fetch AI (Ep. 161)

    In this episode Fetch AI CTO Jonathan Ward speaks about decentralization, AI, blockchain for smart cities and the enterprise.

    Below some great links about collective learning, smart contracts in Rust and the Fetch AI ecosystem.

    • Decentralised collective learning: https://github.com/fetchai/colearn
  • Smart contracting platform written in Rust https://docs.cosmwasm.com/docs/0.14/
  • Fetch.ai cosmwasm contracts for collective learning: https://github.com/fetchai/contract-learn
  • How the Colearn system works: https://vimeo.com/440365943
  • 33 min
  • Apache Arrow, Ballista and Big Data in Rust with Andy Grove RB (Ep. 160)

    Do you want to know the latest in big data analytics frameworks? Have you ever heard of Apache Arrow? Rust? Ballista? In this episode I speak with Andy Grove one of the main authors of Apache Arrow and Ballista compute engine.

    Andy explains some challenges while he was designing the Arrow and Ballista memory models and he describes some amazing solutions.

     
    Our Sponsors

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    Amethix use advanced Artificial Intelligence and Machine Learning to build data platforms and predictive engines in domain like finance, healthcare, pharmaceuticals, logistics, energy. Amethix provide solutions to collect and secure data with higher transparency and disintermediation, and build the statistical models that will support your business.

     

    References

     

    https://arrow.apache.org/

     

    https://ballistacompute.org/

     

    https://github.com/ballista-compute/ballista

     

     

     

     

    30 min
  • GitHub Copilot: yay or nay? (Ep. 159)

    It made already quite some noise in the news, GitHub copilot promises to be your pair programmer for life.

    In this episode I explain how and what GitHub copilot does. Should developers be happy, scared or just keep coding the traditional way?

     

    Sponsors

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    33 min
  • Pandas vs Rust [RB] (Ep. 158)
    Sponsors

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    32 min
  • A simple trick for very unbalanced data (Ep. 157)

    Data from the real world are never perfectly balanced. In this episode I explain a simple yet effective trick to train models with very unbalanced data. Enjoy the show!


    Sponsors

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    References
    • Leo Breiman, Random Forests, 2001
  • C. Chen, A. Liaw, L. Breiman, Using Random Forest to Learn Imbalanced Data (2004)
  •  

    23 min
  • Time to take your data back with Tapmydata (Ep. 156)
    In this episode I am with Gilbert Hill, head of strategy at https://tapmydata.com/
    We speak about personal data, blockchain and the ability to control it and monetize with another simple yet effective app in the ecosystem.
     
     
    References
    • https://tapmydata.com/
  • https://medium.com/@tholder/we-dont-want-your-data-pushing-boundaries-in-data-collection-and-end-to-end-encryption-for-apps-ebd1d5f79df5
  • 42 min

About Data Science at Home

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Cutting through AI bullsh*t.
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