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All Blog Posts Tagged 'Neural' (22)

Machine Learning on Mobile: An On-device Inference App for Skin Cancer Detection

Mobile health (mHealth) is considered one of the most transformative drivers for health informatics delivery of ubiquitous medical applications. Machine learning has proven to be a powerful tool in classifying medical images for detecting various diseases. However, supervised machine learning requires a large amount of data to train the model, whose storage and processing pose considerable system requirements challenges for mobile applications. Therefore, many studies focus on…

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Added by AI on August 16, 2019 at 6:00am — No Comments

[New] Handbook of Deep Learning Applications (Springer)

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artifacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique…

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Added by Sanjiban Sekhar Roy on March 1, 2019 at 11:30pm — No Comments

Convolutional Neural Network  (CNN) From Scratch

Introduction

In a regular neural network, the input is transformed through a series of hidden layers having multiple neurons. Each neuron is connected to all the neurons in the previous and the following layers. This arrangement is called a fully connected layer and the last layer is the output layer. In Computer Vision applications where the input is an image, we use convolutional neural network…

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Added by Muhammad Rizwan on September 24, 2018 at 3:00pm — No Comments

Model Serving: Stream Processing vs. RPC / REST - A Deep Learning Example with TensorFlow and Kafka

Machine Learning / Deep Learning models can be used in different ways to do predictions. My preferred way is to deploy an analytic model directly into a stream processing application (like Kafka Streams or KSQL). You could e.g. use the …

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Added by Kai Waehner on July 8, 2018 at 4:26pm — No Comments

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

5 Hot AI & Machine Learning Trends for 2018

The mantra for technology evolution has been to replace or minimize human assistance with machines. Traditionally human support systems are rapidly being replaced by machines & by automation. The dependence on human decision-making is shrinking fast. If we take a domestic cooking gas stove as an example, we now have the automated safety gas stove where the gas supply can be cut off completely by itself in case of gas leakage or mishandling, thus avoiding fatal accidents and…

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Added by Yuvan Asav on March 27, 2018 at 10:00pm — No Comments

Credit Risk Prediction Using Artificial Neural Network Algorithm

1 Introduction

Credit risk or credit default indicates the probability of non-repayment of bank financial services that have been given to the customers. Credit risk has always been an extensively studied area in bank lending decisions. Credit risk plays a crucial role for banks and financial institutions, especially for commercial banks and it is always difficult to interpret and manage. Due to the advancements in technology, banks have managed to reduce the costs, in order to…

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Added by Shruti Goyal on March 14, 2018 at 11:30am — 5 Comments

Neural network classification of data using Smile

Data classification is the central data-mining technique used for sorting data, understanding of data and for performing outcome predictions. In this small blog we will use a library Smilecthat includes many methods for supervising and non-supervising data classification…

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Added by jwork.ORG on March 13, 2018 at 4:00pm — No Comments

Email Classification into relevant labels using Neural Networks

This research work has been carried out jointly by Deepak Kumar Gupta & Shruti Goyal November 11, 2017

Abstract

In the real world, many online shopping websites or service provider have single email-id where customers can send their…

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Added by Deepak Kumar Gupta on March 10, 2018 at 1:30pm — No Comments

Machine Learning Techniques based paper one of the two Risk Quant Europe 2018 Call for Paper Winners

Each year, Risk Quant Europe Conference, a conference well-attended by practitioners from banking, asset management, insurers as well as academics from Europe, selects two papers to present in their annual conference.

For 2018, our paper is lucky to be one of the two winning papers selected by the Advisory Board for the conference to be held in London. Please feel free to check out our paper titled CDS Rate Construction Methods by Machine Learning…

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Added by Zhongmin Luo on February 24, 2018 at 2:00am — No Comments

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

Understanding Neural Network: A beginner’s guide

Neural network or artificial neural network is one of the frequently used buzzwords in analytics these days. Neural network is a machine learning technique which enables a computer to learn from the observational data. Neural network in computing is inspired by the way biological nervous system process information.

Biological neural networks consist of…

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Added by Ashish Sukhadeve on August 6, 2017 at 7:00am — 45 Comments

A Guide for Applying Machine Learning Techniques in Finance

Does it sound familiar to you? In order to get an idea of how to choose a parameter for a given classifier, you have to cross reference to a number of papers or books, which often turn out to present competing arguments for or against a certain parameterization choice but with few applications to real-world problems.

For example, you may find a few papers discussing optimal selection of K in…

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Added by Zhongmin Luo on June 5, 2017 at 7:30pm — 6 Comments

Choice of K in K-fold Cross Validation for Classification in Financial Market

Cross Validation is often used as a tool for model selection across classifiers. As discussed in detail in the following paper https://ssrn.com/abstract=2967184, Cross Validation is typically performed in the following steps:

  • Step 1: Divide the original sample into K sub samples; each subsample typically has equal sample size and is referred to as one fold, altogether,…
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Added by Zhongmin Luo on June 2, 2017 at 7:00pm — No Comments

Parameter Selection in Classification for Financial Market

In practice, we often have to make parameterization choices for a given classifier in order to achieve optimal classification performances; just to name a few examples:

  • Neural Network: e.g., the optimal choice of Activation Functions, # of hidden units
  • Support Vector Machine: e.g., the optimal choice of Kernel Functions
  • Ensemble: e.g., the number of Learning Cycles for Bagging.
  • Discriminant Analysis: e.g., Linear/Quadratic; regularization…
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Added by Zhongmin Luo on May 29, 2017 at 12:49am — No Comments

Apply Machine Learning Techniques to Problems in Financial Market

Past literature show that the comparisons of classifier's performance are specific to the types of datasets (e.g., Pharmaceutical industry data) used; i.e., some classifiers may perform better in some context than others. A paper titled CDS Rate Construction Methods by Machine Learning Techniques conducts the performance comparison exclusively in the context of financial market by applying a wide range of classifiers to provide solution to so-called Shortage of…

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Added by Zhongmin Luo on May 23, 2017 at 1:30am — 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

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