Data Science Decoded
Mike EWe discuss seminal mathematical papers (sometimes really old đ ) that have shaped and established the fields of machine learning and data science as we know them today. The goal of the podcast is to introduce you to the evolution of these fields from a mathematical and slightly philosophical perspective. We will discuss the contribution of these papers, not just from pure a math aspect but also h... more
| Publishes | Infrequently | Episodes | 34 | Founded | a year ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | ScienceMathematics | |||
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Latest Episodes
On the 34th episode, we review the 1986 paper, "Learning representations by back-propagating errors" , which was pivotal because it provided a clear, generalized framework for training neural networks with internal 'hidden' units. The core of the pro... more
On the 33rd episdoe we review Paul Werbosâs âApplications of Advances in Nonlinear Sensitivity Analysisâ which presents efficient methods for computing derivatives in nonlinear systems, drastically reducing computational costs for large-scale models.... more
We reviewed Richard Bellmanâs âA Markovian Decision Processâ (1957), which introduced a mathematical framework for sequential decision-making under uncertainty.
By connecting recurrence relations to Markov processes, Bellman showed how current choi... more
On the 31st episode of the podcast, we add Liron to the team, we review a gem from 1921, where Sewall Wright introduced path analysis, mapping hypothesized causal arrows into simple diagrams and proving that any sample correlation can be written as t... more
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- Podcast is good but please:
Donât breathe or cough in that damn microphone!
Props for the work done.
Apple Podcasts4Orlac2
Italy5 months ago
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Apple Podcasts | #7 |  United States/Science/Mathematics |
Apple Podcasts | #5 |  United Kingdom/Science/Mathematics |
Apple Podcasts | #9 |  Canada/Science/Mathematics |
Apple Podcasts | #240 | Canada/Science |
Apple Podcasts | #4 |  Germany/Science/Mathematics |
Apple Podcasts | #16 | Italy/Science/Mathematics |
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Frequently Asked Questions About Data Science Decoded
What is Data Science Decoded about and what kind of topics does it cover?
The content revolves around the examination of influential mathematical papers that have significantly contributed to the development of data science and machine learning. Each episode engages in an in-depth analysis of these seminal works, exploring not only the mathematical principles but also their broader implications within the academic and professional spheres. The discussions often take a philosophical turn, reflecting on how these papers have shaped the evolution of various methodologies and opened new avenues for research and application in the fields. By tracing the historical context and impact of these foundational works, the episodes aim to make complex mathematical concepts accessible and relevant to both practitioners and ent... more
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Which podcasts are similar to Data Science Decoded?
These podcasts share a similar audience with Data Science Decoded:
1. Super Data Science: ML & AI Podcast with Jon Krohn
2. Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
3. Conversations with Tyler
4. Machine Learning Street Talk (MLST)
5. Dwarkesh Podcast
How many episodes of Data Science Decoded are there?
Data Science Decoded launched a year ago and published 34 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.
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