ML Ops Best Practices

1

Data Skeptic book giveaway contest winner selection

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2

OpenHouse - Front end and API overview

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3

OpenHouse Crawling with AWS Lambda

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[MINI] Logistic Regression on Audio Data

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5

Data Provenance and Reproducibility with Pachyderm

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[MINI] Primer on Deep Learning

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7

Big Data Tools and Trends

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8

[MINI] Automated Feature Engineering

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9

The Data Refuge Project

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10

[MINI] The Perceptron

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11

[MINI] Feed Forward Neural Networks

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Data Science at Patreon

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13

[MINI] Backpropagation

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[MINI] GPU CPU

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OpenHouse

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[MINI] Generative Adversarial Networks

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[MINI] AdaBoost

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[MINI] The Bootstrap

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[MINI] Dropout

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[MINI] Gini Coefficients

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21

[MINI] Random Forest

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[MINI] Heteroskedasticity

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23

[MINI] ANOVA

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24

Urban Congestion

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25

[MINI] The CAP Theorem

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26

Unstructured Data for Finance

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27

Detecting Terrorists with Facial Recognition?

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28

Predictive Models on Random Data

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29

[MINI] Entropy

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30

[MINI] F1 Score

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31

Causal Impact

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32

Machine Learning on Images with Noisy Human-centric Labels

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33

The Library Problem

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34

Stealing Models from the Cloud

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35

Data Science at eHarmony

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36

Multiple Comparisons and Conversion Optimization

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37

Election Predictions

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38

[MINI] Calculating Feature Importance

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39

MS Connect Conference

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40

Music21

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41

The Police Data and the Data Driven Justice Initiatives

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42

Studying Competition and Gender Through Chess

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43

[MINI] Goodhart's Law

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44

Trusting Machine Learning Models with LIME

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45

[MINI] Leakage

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46

Predictive Policing

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47

Mutli-Agent Diverse Generative Adversarial Networks

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48

[MINI] Convolutional Neural Networks

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49

Unsupervised Depth Perception

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50

[MINI] Max-pooling

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51

MS Build 2017

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52

Activation Functions

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53

Doctor AI

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54

[MINI] The Vanishing Gradient

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55

CosmosDB

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56

Estimating Sheep Pain with Facial Recognition

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57

[MINI] Conditional Independence

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58

MINI: Bayesian Belief Networks

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59

Project Common Voice

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60

[MINI] Recurrent Neural Networks

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