Data Science at Patreon

Data Skeptic · Intermediate ·📄 Research Papers Explained ·9y ago
  In this week's episode of Data Skeptic, host Kyle Polich talks with guest Maura Church, Patreon's data science manager. Patreon is a fast-growing crowdfunding platform that allows artists and creators of all kinds build their own subscription content service. The platform allows fans to become patrons of their favorite artists- an idea similar the Renaissance times, when musicians would rely on benefactors to become their patrons so they could make more art. At Patreon, Maura's data science team strives to provide creators with insight, information, and tools, so that creators can focus on what they do best-- making art. On the show, Maura talks about some of her projects with the data science team at Patreon. Among the several topics discussed during the episode include: optical music recognition (OMR) to translate musical scores to electronic format, network analysis to understand the connection between creators and patrons, growth forecasting and modeling in a new market, and churn modeling to determine predictors of long time support. A more detailed explanation of Patreon's A/B testing framework can be found here Other useful links to topics mentioned during the show: OMR research Patreon blog Patreon HQ blog Amanda Palmer Fran Meneses
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Playlist

Uploads from Data Skeptic · Data Skeptic · 12 of 60

1 Data Skeptic book giveaway contest winner selection
Data Skeptic book giveaway contest winner selection
Data Skeptic
2 OpenHouse - Front end and API overview
OpenHouse - Front end and API overview
Data Skeptic
3 OpenHouse Crawling with AWS Lambda
OpenHouse Crawling with AWS Lambda
Data Skeptic
4 [MINI] Logistic Regression on Audio Data
[MINI] Logistic Regression on Audio Data
Data Skeptic
5 Data Provenance and Reproducibility with Pachyderm
Data Provenance and Reproducibility with Pachyderm
Data Skeptic
6 [MINI] Primer on Deep Learning
[MINI] Primer on Deep Learning
Data Skeptic
7 Big Data Tools and Trends
Big Data Tools and Trends
Data Skeptic
8 [MINI] Automated Feature Engineering
[MINI] Automated Feature Engineering
Data Skeptic
9 The Data Refuge Project
The Data Refuge Project
Data Skeptic
10 [MINI] The Perceptron
[MINI] The Perceptron
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11 [MINI] Feed Forward Neural Networks
[MINI] Feed Forward Neural Networks
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Data Science at Patreon
Data Science at Patreon
Data Skeptic
13 [MINI] Backpropagation
[MINI] Backpropagation
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14 [MINI] GPU CPU
[MINI] GPU CPU
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15 OpenHouse
OpenHouse
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16 [MINI] Generative Adversarial Networks
[MINI] Generative Adversarial Networks
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17 [MINI] AdaBoost
[MINI] AdaBoost
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18 [MINI] The Bootstrap
[MINI] The Bootstrap
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19 [MINI] Dropout
[MINI] Dropout
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20 [MINI] Gini Coefficients
[MINI] Gini Coefficients
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21 [MINI] Random Forest
[MINI] Random Forest
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22 [MINI] Heteroskedasticity
[MINI] Heteroskedasticity
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23 [MINI] ANOVA
[MINI] ANOVA
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24 Urban Congestion
Urban Congestion
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25 [MINI] The CAP Theorem
[MINI] The CAP Theorem
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26 Unstructured Data for Finance
Unstructured Data for Finance
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27 Detecting Terrorists with Facial Recognition?
Detecting Terrorists with Facial Recognition?
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28 Predictive Models on Random Data
Predictive Models on Random Data
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29 [MINI] Entropy
[MINI] Entropy
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30 [MINI] F1 Score
[MINI] F1 Score
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31 Causal Impact
Causal Impact
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32 Machine Learning on Images with Noisy Human-centric Labels
Machine Learning on Images with Noisy Human-centric Labels
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33 The Library Problem
The Library Problem
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34 Stealing Models from the Cloud
Stealing Models from the Cloud
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35 Data Science at eHarmony
Data Science at eHarmony
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36 Multiple Comparisons and Conversion Optimization
Multiple Comparisons and Conversion Optimization
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37 Election Predictions
Election Predictions
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38 [MINI] Calculating Feature Importance
[MINI] Calculating Feature Importance
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39 MS Connect Conference
MS Connect Conference
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40 Music21
Music21
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41 The Police Data and the Data Driven Justice Initiatives
The Police Data and the Data Driven Justice Initiatives
Data Skeptic
42 Studying Competition and Gender Through Chess
Studying Competition and Gender Through Chess
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43 [MINI] Goodhart's Law
[MINI] Goodhart's Law
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44 Trusting Machine Learning Models with LIME
Trusting Machine Learning Models with LIME
Data Skeptic
45 [MINI] Leakage
[MINI] Leakage
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46 Predictive Policing
Predictive Policing
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47 Mutli-Agent Diverse Generative Adversarial Networks
Mutli-Agent Diverse Generative Adversarial Networks
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48 [MINI] Convolutional Neural Networks
[MINI] Convolutional Neural Networks
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49 Unsupervised Depth Perception
Unsupervised Depth Perception
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50 [MINI] Max-pooling
[MINI] Max-pooling
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51 MS Build 2017
MS Build 2017
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52 Activation Functions
Activation Functions
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53 Doctor AI
Doctor AI
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54 [MINI] The Vanishing Gradient
[MINI] The Vanishing Gradient
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55 CosmosDB
CosmosDB
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56 Estimating Sheep Pain with Facial Recognition
Estimating Sheep Pain with Facial Recognition
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57 [MINI] Conditional Independence
[MINI] Conditional Independence
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58 MINI: Bayesian Belief Networks
MINI: Bayesian Belief Networks
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59 Project Common Voice
Project Common Voice
Data Skeptic
60 [MINI] Recurrent Neural Networks
[MINI] Recurrent Neural Networks
Data Skeptic

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