Data Science Decoded

Data Science Decoded

Podcast 🎧 Listen on Apple Podcasts Mathematics
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Ratings
6
Avg rating
★ 4 /5
Episodes
34
Cadence
0.2 ep/wk
Latest episode
8 months ago
🧰 Free analysis for Data Science Decoded
🕵️ Fake follower check 📊 Engagement rate 💰 What they charge

💡 Facts

📤Posts about 0.2× per week.

👥 Audience demographics

Estimated

Modeled from this creator's niche, platform & region — a planning estimate, not connected analytics.

Gender split
Male 50% Female 50%
Age · peak 18-24
13-1710%
18-2432%
25-3431%
35-4415%
45+12%
Top geographies
  • United States34%
  • India11%
  • United Kingdom8%
  • Brazil6%
  • Indonesia5%
Likely interests
EntertainmentLifestyleTrending

About

We discuss seminal mathematical papers (sometimes really old 😎 ) 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 how they influenced the discourse in the field, which areas were opened up as a result, and so on. Our podcast episodes are also available on our youtube: https://youtu.be/wThcXx_vXjQ?si=vnMfs

📸 Gallery

Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985) Data Science #33 - The Backpropagation method, Paul Werbos (1980) Data Science #32 - A Markovian Decision Process, Richard Bellman (1957) Data Science #31 - Correlation and causation (1921), Wright Sewall Data Science #30 - The Bootstrap Method (1977) Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979) Data Science #28 - The Bloom filter algorithm Data Science #27 - The History of Least Squares (1877)

Recent content

Data Science #34 - The deep learning original paper review, Hinton, Rumelhard & Williams (1985)
8 months ago
Data Science #33 - The Backpropagation method, Paul Werbos (1980)
8 months ago
Data Science #32 - A Markovian Decision Process, Richard Bellman (1957)
10 months ago
Data Science #31 - Correlation and causation (1921), Wright Sewall
1 year ago
Data Science #30 - The Bootstrap Method (1977)
1 year ago
Data Science #29 - The Chi-square automatic interaction detection(CHAID) algorithm (1979)
1 year ago
Data Science #28 - The Bloom filter algorithm
1 year ago
Data Science #27 - The History of Least Squares (1877)
1 year ago
Data Science #26 - The First Gradient decent algorithm by Cauchy (1847)
1 year ago
Data Science #24 - The Expectation Maximization (EM) algorithm Paper review (1977)
1 year ago
Data Science #23- The Markov Chain Monte Carl MCMC Paper review (1953)
1 year ago
Data Science #22 - The theory of dynamic programming, Paper review 1954
1 year ago

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

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