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 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)  

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

True Machine Intelligence just like the human brain (Ep. 155)

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