Data Science at Home

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.     Sponsored by Quantum Metric Did you know that 2021 holiday ecommerce sales are expected to exceed 2020 benchmarks?
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With Quantum Metric, you can be. Visit their website at quantummetric.com/podoffer and see if you qualify to receive their “12 Days of Insights” offer with code DATASCIENCE. This offer gives you 12-day access to the platform coupled with a bespoke insight report that will help you identify where customers are struggling or engaging in your digital product.      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/

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    

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...   Sponsors Get one of the best VPN at a massive discount with coupon code DATASCIENCE. It provides you with an 83% discount which unlocks the best price in the market plus 3 extra months for free. Here is the link https://surfshark.deals/DATASCIENCE

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

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 If building software is your passion, you’ll love ThoughtWorks Technology Podcast. It’s a podcast for techies by techies. Their team of experienced technologists take a deep dive into a tech topic that’s piqued their interest — it could be how machine learning is being used in astrophysics or maybe how to succeed at continuous delivery.   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        

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 Get one of the best VPN at a massive discount with coupon code DATASCIENCE. It provides you with an 83% discount which unlocks the best price in the market plus 3 extra months for free. Here is the link https://surfshark.deals/DATASCIENCE

Sponsors Get one of the best VPN at a massive discount with coupon code DATASCIENCE. It provides you with an 83% discount which unlocks the best price in the market plus 3 extra months for free. Here is the link https://surfshark.deals/DATASCIENCE    

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 Get one of the best VPN at a massive discount with coupon code DATASCIENCE. It provides you with an 83% discount which unlocks the best price in the market plus 3 extra months for free. Here is the link https://surfshark.deals/DATASCIENCE   References Leo Breiman, Random Forests, 2001 C. Chen, A. Liaw, L. Breiman, Using Random Forest to Learn Imbalanced Data (2004)  

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

In this episode I have a really interesting conversation with Karan Grewal, member of the research staff at Numenta where he investigates how biological principles of intelligence can be translated into silicon. We speak about the thousand brains theory and why neural networks forget.     References Main paper on the Thousand Brains Theory: https://www.frontiersin.org/articles/10.3389/fncir.2018.00121/full Blog post on Thousand Brains Theory: https://numenta.com/blog/2019/01/16/the-thousand-brains-theory-of-intelligence/ GLOM paper by Geoff Hinton: https://arxiv.org/pdf/2102.12627.pdf Why neural networks forget? https://numenta.com/blog/2021/02/04/why-neural-networks-forget-and-lessons-from-the-brain