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All Blog Posts Tagged 'Networks' (13)

Debunking Google's Death AI

Having my newsfeed cluttered with articles about Google creating an AI that beats hospitals by predicting death with 95% accuracy (or some other erroneous claim), I dug up the original research paper to fact check this wondrous new advancement. Many of said articles used this quote from the abstract (academia's equivalent of a paperback blurb):

These…
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Added by Stephen Chen on July 4, 2018 at 1:30am — 1 Comment

New Marketing Insight from Unsupervised Bayesian Belief Networks

Introduction

“Limited-Service Restaurants” (LSRs) is how the restaurant industry refers collectively to fast food and fast-casual dining establishments.  Marketers who specialize in LSRs often employ marketing research to evaluate hypotheses about their brands or to detect segments within their markets.  An important additional purpose of market research is to understand the total structure of a market, to find out what guests consider important…

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Added by Charles Hammerslough on February 20, 2018 at 10:30am — 1 Comment

Image Processing and Neural Networks Intuition: Part 1

In this series, I will talk about training a simple neural network on image data. To give a brief overview, neural networks is a kind of supervised learning. By this I mean, the model needs to train on historical data to understand the relationship between input variables and target variables. Once trained, the model can be used to predict target variable on new input data. In the previous posts, we have written about linear, lasso and ridge regression. All those methods come under…

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Added by Jobil Louis on January 16, 2018 at 8:00pm — No Comments

Inside the black box 2

Following the original observations of Neural Networks in action; I decided a follow up was needed.  In the original blog, ; the smallest neural net (NN) that learnt the data set was 2-6-3-1 but the details were not saved, a second NN with the same configuration came close but its approach was different. The…

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Added by Sierra Oscar on January 4, 2018 at 10:09am — No Comments

Inside the black box

Introduction

This post is designed show the internal changes of an Artificial Neural Network (ANN/NN), it shows the outputs of the neurons from the beginning of a Backpropagation algorithm to convergence.

The hope is for a better understanding of why we use a second hidden layer, local minimums, to how many internal nodes are required and their impact on the final solution.

The Dataset…

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Added by Sierra Oscar on November 15, 2017 at 9:33pm — No Comments

Artificial Intelligence is not “Fake” Intelligence

Quick quiz!

What’s the first thing that comes to mind when you hear the following phrases?

  • Artificial grass
  • Artificial sweeteners
  • Artificial flavors
  • Artificial plants
  • Artificial flowers
  • Artificial diamonds and jewelry
  • Artificial (fake) news

These phrases probably evoke thoughts such as “fake,” “not real,” or even “shabby.” Artificial is such a harsh adjective.…

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Added by Bill Schmarzo on October 30, 2017 at 6:30pm — No Comments

Generative Adversarial Networks (GANs): Engine and Applications


Generative adversarial networks (GANs) are a class of neural networks that are used in unsupervised machine learning. They help to solve such tasks as image generation from descriptions, getting high resolution images from low resolution ones, predicting which drug…

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Added by Luba Belokon on August 17, 2017 at 6:30am — No Comments

Yet another introduction to Neural Networks

There are many great tutorials on neural networks that one can find online nowadays. Simply searching for the words “Neural Network” will produce numerous results on GithubGist. Even tough there are many examples floating around on the web, I decided to have my own Introduction to Neural Networks!

In my tutorial, I specifically  tried to illustrate the use of Python classes to define layers in the network as objects. Each layer object has forward and backward propagation methods which…

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Added by Burak Himmetoglu on February 7, 2017 at 2:30pm — 3 Comments

Generative Adversarial Networks (GANs) Explained in Layman Terms

 

NIPS2016 (Neural Information Processing System) is an annual event that attracts the best and the brightest of the field of Machine Learning both from academia as well as industry. I attended this event last week for the very first time and was blown away by the volume and diversity of the presentations. One unusual observation…

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Added by Al Gharakhanian on December 22, 2016 at 1:00pm — 1 Comment

Deep Learning with Professor Geoff Hinton

This video session features the keynote speaker Professor Geoff Hinton FRS, “Deep Learning”. This lecture was filmed on May 22, 2015.

Watch full video at …

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Added by Diego Marinho de Oliveira on April 4, 2016 at 5:32am — No Comments

Self-learning Machines & Deep Convolutional Neural Networks Classify Scenes & Identify Objects

Recent research using deep convolutional neural networks and new system architectures have demonstrated the ability of smart machines to…

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Added by Michael Walker on May 16, 2015 at 2:38pm — 1 Comment

Implementing a Distributed Deep Learning Network over Spark

Implementing a Distributed Deep Learning Network over Spark

Authors: Dr. Vijay Srinivas Agneeswaran, Director and Head, Big Data Labs, Impetus {[email protected]}

Ghousia Parveen Taj, Lead Software Engineer, Impetus { [email protected]}

Sai Sagar, Software Engineer, Impetus {[email protected]}

Padma Chitturi, Software Engineer,…

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Added by Dr. Vijay Srinivas Agneeswaran on November 25, 2014 at 1:30am — 6 Comments

Markov Logic Networks for Better Decisions

One important goal of data science is to help decision makers make better decisions. …

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Added by Michael Walker on January 15, 2014 at 12:24pm — 1 Comment

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