[MINI] Backpropagation

Data Skeptic · Advanced ·📐 ML Fundamentals ·9y ago
Backpropagation is a common algorithm for training a neural network.  It works by computing the gradient of each weight with respect to the overall error, and using stochastic gradient descent to iteratively fine tune the weights of the network.  In this episode, we compare this concept to finding a location on a map, marble maze games, and golf.
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Uploads from Data Skeptic · Data Skeptic · 13 of 60

1 Data Skeptic book giveaway contest winner selection
Data Skeptic book giveaway contest winner selection
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2 OpenHouse - Front end and API overview
OpenHouse - Front end and API overview
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3 OpenHouse Crawling with AWS Lambda
OpenHouse Crawling with AWS Lambda
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4 [MINI] Logistic Regression on Audio Data
[MINI] Logistic Regression on Audio Data
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5 Data Provenance and Reproducibility with Pachyderm
Data Provenance and Reproducibility with Pachyderm
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6 [MINI] Primer on Deep Learning
[MINI] Primer on Deep Learning
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7 Big Data Tools and Trends
Big Data Tools and Trends
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8 [MINI] Automated Feature Engineering
[MINI] Automated Feature Engineering
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9 The Data Refuge Project
The Data Refuge Project
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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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12 Data Science at Patreon
Data Science at Patreon
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[MINI] Backpropagation
[MINI] Backpropagation
Data Skeptic
14 [MINI] GPU CPU
[MINI] GPU CPU
Data Skeptic
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
Data Skeptic
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
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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
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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
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60 [MINI] Recurrent Neural Networks
[MINI] Recurrent Neural Networks
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