CNN Model of Image Detection in Keras (TensorFlow) in Python3

This article covers the basic application of Keras and CNN in Python3, with Sublime text3 and Ipython Notebook as IDE. More details of the following code can be found in Robert Layton’s book here: https://www.goodreads.com/book/show/26019855-learning-data-mining-with-python?from_search=true ###The book above said that we will build a system that will take an image as an input ###and give […]

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Keras in Python, Backend TensorFlow, with Iris data to Build Deep Learning Model

We talked about Deep Learning Modeling in TensorFlow in Python&R: https://charleshsliao.wordpress.com/2017/06/06/rnn-in-tensorflow-in-pythonr-with-mnist/ We also mentioned Keras application in R: https://charleshsliao.wordpress.com/2017/04/24/cnndnn-of-keras-in-r-backend-tensorflow-for-mnist/ This article covers the basic application of Keras and TensorFlow in Python3, with Sublime text3 and Ipython Notebook as IDE. More details of the following code can be found in Robert Layton’s book here: https://www.goodreads.com/book/show/26019855-learning-data-mining-with-python?from_search=true ###This […]

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Epic’s Tim Sweeney: Deep Learning A.I. Will Open New Frontiers in Game Design

“[Video game] AI is still in the dark ages,” Epic CEO Tim Sweeney told a crowd gathered for Games Beat’s 2017 industry summit. The video game industry has witness a tremendous amount of growth, thanks to the incredible increase in computation power in terms of visual representations. Using the parallel computation ability of GPUs, powerful […]

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Generating ROC curve in SCALA from H2O binary classification models

You can use the following blog to built a binomial classification  GLM model: https://aichamp.wordpress.com/2017/04/23/binomial-classification-example-in-scala-and-gbm-with-h2o/ To collect model metrics  for training use the following: val trainMetrics = ModelMetricsSupport.modelMetrics[ModelMetricsBinomial](glmModel, train) Now you can access model AUC (_auc object) as below: Note: _auc object has array of thresholds, and then for each threshold it has fps and tps (use […]

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RNN in TensorFlow in Python&R, with MNIST

Thought it is more convenient to conduct TensorFlow framework in python, we also talked about how to imply Tensorflow in R here:https://charleshsliao.wordpress.com/tag/tensorflow/ We will talk about how to apply Recurrent neural network in TensorFlow on both of python and R. in R: #1. We load the data library(tensorflow) mnist<-tf$contrib$learn$datasets$mnist$load_mnist(train_dir = “MNIST-data”) #2.Identify Essential Parameters Input<-28L […]

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RE·WORK: Deep Learning in Retail Summit (London, UK)

Background: RE•WORK is one of the top global Machine Intelligence industry conference/summit organizers. The aim of Rework: Combining entrepreneurship, technology & science to re-work the future. Time: 6.1-6.2 2017 Location: ETC Venues 155 Bishopsgate Liverpool St London EC2M 3YD Introduction for this Rework conference: In general, Rework summit will invite extraordinary speakers to discover advances […]

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C2 Montreal – Master Class with Yoshua Bengio: Know The Basics

Held May 23-25, C2 Montréal 2017 attracted over 6,000 industry participants from 50 countries. Now in its 6th year, organizers of the “immersive event” partnered with local startup Element AI to host Canada’s first Artificial Intelligence Forum and promote Montréal as a global AI hub. The keynote speakers were Professor Yoshua Bengio of the Montreal […]

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Deep Learning Software Revenues to Reach $35 Billion in 2025

Tractica: Top 10 use cases for deep learning, in terms of revenue, will be as follows: Static image recognition, classification, and tagging Machine/vehicular object detection/identification/avoidance Patient data processing Algorithmic trading strategy performance improvement Converting paperwork into digital data Medical image analysis Localization and mapping Sentiment analysis Social media publishing and management Intelligent recruitment and HR […]

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Data science and deep learning in retail

[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Jeremy Stanley on hiring and leading machine learning engineers to build world-class data products. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, […]

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