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Ethical Machine Learning
www.ethicalmachinelearning.com/
ML technologies don't have to be intrusive and surveillance-like. Let's get back to make people's lives better

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ML technologies don't have to be intrusive and surveillance-like. Let's get back to make people's lives better

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External links in ethicalmachinelearning.com

  • link https://twitter.com/intent/tweet?url=https%3A%2F%2Ftmblr.co%2FZEcg8f2F_50pE&text=From 0 to face detection: Computer Vision Tutorial with Convolutional Neural Networks%20-%20
  • link http://www.facebook.com/sharer/sharer.php?s=100&p[url]=https%3A%2F%2Ftmblr.co%2FZEcg8f2F_50pE&p[title]=From 0 to face detection: Computer Vision Tutorial with Convolutional Neural Networks&p[images][0]=http://assets.tumblr.com/images/og/text_200.png&p[summary]=Introduction How hard is it for a complete newbie to learn how to do some interesting machine learning? It turns out, with the current state of tooling - not very. In this post, I will discuss a complete deep learning solution for the computer vision task of face detection. Face detection is an interesting task which boils down to: detect how many faces are in a given image; detect where they are as accurately as possible. This has obvious surveillance and security applications (…yay?), but it can also be used in complex multimedia information retrieval. But more about this later :) Convolutional Neural Networks A Convolutional Neural Network (CNN from here onwards) is a neural network with a “deep” architecture, i.e. with more than one hidden layer. CNNs are inspired by biological research on animals’ visual system, which reveals that the cells in the visual cortex are arranged in a way so that each cell is sensible to a section of the animal’s visible field [1]. For this reason they are expecially used in Computer Vision tasks. Neural Networks Overview The term “neural network” refers to a broad family of models that are inspired by the human neuron. They are often used to undertake supervised machine learning problems, but there are a number of models that also manage learning with a unsupervised dataset. There are at least three elements that are needed to define a Neural Network model: An architecture: defining how many neurons are in the model and how they are connected. Usually, the connections between neurons are weighted, and those weights are the parameters of a neural network. An activation rule: a function that determines how the neuron outputs values. In a Perceptron architecture a neuron can either be activated (output value 1) or not (output value 0), but that’s not the case in a Convolutional Neural Network. An update rule: a function that modifies the weights of the connections over time by looking at the final performance of the network. Keep reading
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  • link http://www.ethicalmachinelearning.com/
  • link http://www.ethicalmachinelearning.com/post/154586582222/from-0-to-face-detection-computer-vision-tutorial

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Domain Name: ETHICALMACHINELEARNING.COM
Registry Domain ID: 2081583869_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.enom.com
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Updated Date: 2017-03-10T17:48:01Z
Creation Date: 2016-12-13T19:11:12Z
Registry Expiry Date: 2017-12-13T19:11:12Z
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Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
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DNSSEC: unsigned
URL of the ICANN Whois Inaccuracy Complaint Form: https://www.icann.org/wicf/
>>> Last update of whois database: 2017-09-03T12:42:54Z

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