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Great Reads

by Thomas Weller
Demonstrates how to run Python scripts from C#
by Dmitriy Gakh
The perspectives of creating bots that write programs with two simple examples.
by Andy Allinger
Adds features to k-means for missing data, mixed data, and choosing the number of clusters
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating convolutional ANNs and applying them to image classification tasks.

Latest Articles

by Abdulkader Helwan
In this article, we show you how to set up an Android Studio environment that is suitable for loading and running our .tflite model.
by MehreenTahir
In this article we explore how to enrich our data using a pre-trained model and trigger an Auto ML experiment from a Spark table.
by MehreenTahir
In this article we jump right into setting up an Azure Synapse workspace and Azure Synapse Studio to prepare for our machine learning analysis in the next article in the series.
by MehreenTahir
In this article we learn about how Azure Synapse Analytics and Azure Machine Learning help analyze data without extensive coding and ML experience.

All Articles

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Machine Learning 

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28 Jul 2021N
Abdulkader Helwan
In this article, we show you how to set up an Android Studio environment that is suitable for loading and running our .tflite model.
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26 Jul 2021N
MehreenTahir
In this article we explore how to enrich our data using a pre-trained model and trigger an Auto ML experiment from a Spark table.
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23 Jul 2021N
MehreenTahir
In this article we jump right into setting up an Azure Synapse workspace and Azure Synapse Studio to prepare for our machine learning analysis in the next article in the series.
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22 Jul 2021N
MehreenTahir
In this article we learn about how Azure Synapse Analytics and Azure Machine Learning help analyze data without extensive coding and ML experience.
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19 Jul 2021U
Shweta Lodha
This article walks you through the steps required to create a custom ML model, train it and then use the same model to analyze the sales receipt.
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16 Jul 2021
David Norton
In this article we explore how to view and access model data.
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15 Jul 2021
David Norton
In this article we explore how to get data into Azure Synapse Analytics and build a machine learning model.
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13 Jul 2021
David Norton
In this article we outline the problem: our fictional CEO wants to predict taxi use to ensure taxis are available where and when customers need them.
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9 Jul 2021
Shweta Lodha
Ways to extract information from sales receipt and detailed demonstration of how to use pre-built ML models
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2 Jul 2021
Marcelo Ricardo de Oliveira
In this article we explore how data science and business intelligence teams can use Azure Synapse Analytics data to gain new insight into business processes.
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29 Jun 2021
Marcelo Ricardo de Oliveira
In this article we explore Azure Synapse Analytics and some of its features.
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27 Jun 2021
KristianEkman
How to build an AI which plays Backgammon
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25 May 2021
Jarek Szczegielniak
In this article, we publish our NLP API service to Azure using Azure Container Instances.
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21 May 2021
Jarek Szczegielniak
In this article we use Visual Studio Code to edit and debug our increasingly complex code running inside a Docker container.
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20 May 2021
Jarek Szczegielniak
In this article, we’ll modify our code to expose the same logic via a Rest API service.
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19 May 2021
Jarek Szczegielniak
In this article we run an inference model for NLP using models persisted on a Docker volume.
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18 May 2021
Jarek Szczegielniak
In this article we run inference on sample images with TensorFlow using a containerized Object Detection API environment.
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11 May 2021
Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
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10 May 2021
Sergio Virahonda
In this article we build the model API to support the prediction service.
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7 May 2021
Sergio Virahonda
In this article, we develop a model unit testing container.
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6 May 2021
Sergio Virahonda
In this article, we’ll deep-dive into the Continuous Training code.
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5 May 2021
Sergio Virahonda
In this article, we’ll implement automatic training.
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4 May 2021
Sergio Virahonda
In this article, we set up a cloud environment for this project.
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3 May 2021
Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
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29 Apr 2021
Jarek Szczegielniak
In this article we go back to the Intel/AMD CPUs. This time, we will speed up our calculations using a GPU.
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27 Apr 2021
Jarek Szczegielniak
In this article, we’ll adapt our image for Raspberry Pi with an ARM processor.
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27 Apr 2021
Jarek Szczegielniak
In this article, we’ll create a container to run a CPU inference on the trained model.
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26 Apr 2021
Jarek Szczegielniak
In this article, we’ll start applying our basic Docker knowledge while creating and running containers in the various MLng scenarios.
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23 Apr 2021
Jarek Szczegielniak
In this article – the first one of the series – we’ll go over some Docker basics as they apply to ML applications.
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14 Apr 2021
Martin_Rupp
In this article we introduce the main theoretical concepts required for building an ML-based translator.
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1 Apr 2021
Sergio Virahonda
In this article I’ll show you how to train your deep fake models in the cloud with some help from Docker.
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24 Dec 2020
Andy Allinger
Adds features to k-means for missing data, mixed data, and choosing the number of clusters
10 Dec 2020
Jo Stichbury
In this article we show, a high-level, it is possible to create sophisticated AI-enabled applications that run upon memory-constrained, ultra-low power endpoint devices.
8 Dec 2020
Silvina Bruggia
The COVID-19 pandemic has accelerated machine learning (ML) adoption in many areas, resulting in firms increasing their ML investment and implementation efforts.
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9 Nov 2020
Arnaldo P. Castaño
To end off this series, we will present the alternative of adapting a pre-trained CNN to the coin recognition problem we have been examining all along.
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4 Nov 2020
Arnaldo P. Castaño
In this article we will go over the basics of supervised machine learning and what the training and verification phases consist of.
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2 Oct 2020
philoxenic
In article in this series we will look at even deeper customisation: editing the XML-based model of the figure and then training the result.
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1 Oct 2020
philoxenic
In this article we will try to train our agent to run backwards instead of forwards.
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30 Sep 2020
philoxenic
In this article we will adapt our code to train the Humanoid environment using a different algorithm: Soft Actor-Critic (SAC).
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29 Sep 2020
philoxenic
In this article in the series we start to focus on one particular, more complex environment that PyBullet makes available: Humanoid, in which we must train a human-like agent to walk on two legs.
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28 Sep 2020
philoxenic
In this article, we look at two of the simpler locomotion environments that PyBullet makes available and train agents to solve them.
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25 Sep 2020
philoxenic
In this article, we set up with the Bullet physics simulator as a basis for doing some reinforcement learning in continuous control environments.
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4 Sep 2020
Keith Pijanowski
In this article I provide a brief overview of Keras for those looking for a deep learning framework for building and training neural networks
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3 Sep 2020
Keith Pijanowski
This article is the first in a series of seven articles in which we will explore the value of ONNX with respect to three popular frameworks and three popular programming languages.
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1 Sep 2020
Jarek Szczegielniak
In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.
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31 Aug 2020
Jarek Szczegielniak
In this article we’ll start data preparation for this new, custom model, to be later trained using the Create ML framework.
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28 Aug 2020
Jarek Szczegielniak
Having converted a ResNet model to the Core ML format in the previous article, in this article we’ll now use it in a simple iOS application.
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27 Aug 2020
Jarek Szczegielniak
In this article we'll convert a ResNet model to the Core ML format.
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26 Aug 2020
Jarek Szczegielniak
In this article we prepare our development environment.
19 Aug 2020
David_Oliver
In this article we look at how Refinitiv Labs looks at the real-life challenge faced by equity traders with regards to detecting and responding to unexpected asset price changes.
18 Aug 2020
Joel Sebold
An often neglected — but ultimately fundamental — driver of financial markets is liquidity. Combining data science skills and techniques, the Refinitiv Labs Liquidity Discovery project provides in-depth market liquidity insights to enable more informed trading decisions.
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7 Aug 2020
Arnaldo P. Castaño
In this article we focus on the Text-to-Speech with the use of Deep Learning.
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6 Aug 2020
Arnaldo P. Castaño
In this article we’ll adapt the VGG16 model.
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5 Aug 2020
Arnaldo P. Castaño
In this article we’ll put together our CNN and train it for face recognition.
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4 Aug 2020
Arnaldo P. Castaño
In this article, we’ll talk about preparing a dataset for feeding the correct data to a CNN.
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31 Jul 2020
Arnaldo P. Castaño
In this article, we go over the steps to detect faces in an image.
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23 Jul 2020
Habibur Rony
Basics of the rule-based chatbot, machine-learning chatbot and AI chatbot.
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15 Jul 2020
Raphael Mun
In this article, we will take photos of different hand gestures via webcam and use transfer learning on a pre-trained MobileNet model to build a computer vision AI that can recognize the various gestures in real time.
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14 Jul 2020
Raphael Mun
In this article, we are going to use BodyPix, a body part detection and segmentation library, to try and remove the training step of the face touch detection.
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13 Jul 2020
Raphael Mun
In this article, we are going to use all that we’ve learned so far with computer vision in TensorFlow.js to try building a version of this app ourselves.
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10 Jul 2020
Raphael Mun
In this article we will build a Fluffy Animal Detector, where I will show you a way to leverage a pre-trained Convolutional Neural Network (CNN) model like MobileNet.
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9 Jul 2020
Raphael Mun
In this article, we’ll dive into computer vision running right within a web browser.
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8 Jul 2020
Raphael Mun
In this article, I will show you how quickly and easily set up and use TensorFlow.js to train a neural network to make predictions from data points.
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6 Jul 2020
philoxenic
In this final article in this series, we will look at slightly more advanced topics: minimizing the "jitter" of our Breakout-playing agent, as well as performing grid searches for hyperparameters.
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3 Jul 2020
philoxenic
In this article, we will see how we can improve by approaching the RAM in a slightly different way.
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2 Jul 2020
philoxenic
In this article we will learn from the contents of the game’s RAM instead of the pixels.
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30 Jun 2020
philoxenic
In this article, we will see how you can use a different learning algorithm (plus more cores and a GPU) to train much faster on the mountain car environment.
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29 Jun 2020
philoxenic
In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.
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26 Jun 2020
philoxenic
In this article, we will see what’s going on behind the scenes and what options are available for changing the reinforcement learning.
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25 Jun 2020
philoxenic
In this article, you will be up and running, and will have done your first piece of reinforcement learning.
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23 Jun 2020
Thomas Daniels
In this article we take a quick look at NumPy and TensorFlow also do a short overview of the scikit-learn library.
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22 Jun 2020
Thomas Daniels
In this article, let’s dive into Keras, a high-level library for neural networks.
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19 Jun 2020
Thomas Daniels
In this article we take a look at what you can do with the Natural Language Toolkit (NLTK).
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18 Jun 2020
Thomas Daniels
In this article let's get started hands-on with OpenCV.
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17 Jun 2020
Thomas Daniels
In this article we can take a look at what libraries are available to work on AI and ML tasks.
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16 Jun 2020
Thomas Daniels
In this article we go a bit further with generators and classes.
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15 Jun 2020
Thomas Daniels
Now that you know some of the basics of Python we can go a bit deeper, with the lists and tuples data structures and see how to work with them.
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12 Jun 2020
Thomas Daniels
This article provides some tips for experienced programmers to get up to speed with the basics of Python.
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11 Jun 2020
Glenn Prince
This article gives you a good starting point for your own object detection projects.
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10 Jun 2020
Glenn Prince
In this article, we begin the process of creating a custom object detection model.
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9 Jun 2020
Glenn Prince
In this article, we train our own custom model to detect if people are wearing hardhats.
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8 Jun 2020
Glenn Prince
In this article, we'll have a look at some of the pretrained models we can use in ImageAI to start detecting people in images.
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6 Jun 2020
Alaa Ben Fatma
A visual scripting environment for R & data science.
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5 Jun 2020
Glenn Prince
In this article, we create an object detection model.
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4 Jun 2020
Glenn Prince
In this article, we'll set up everything we need to build a hardhat detector with OpenCV.
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29 May 2020
Jayson DeLancey
This article is the third in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article, we'll look at techniques you can use to start doing the actual NLP analysis.
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29 May 2020
Glenn Prince
This article is the first in the Data Cleaning with Python and Pandas series that helps working developers get up to speed on data science tools and techniques.
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26 Nov 2019
@Abdul Azeez Thekkekandy
This article explores Data Science lifecycles - Business Understanding, Data Understanding and Data Preparation
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5 Nov 2019
Packt Publishing
This post is taken from the book Machine Learning with R - Third Edition, by Packt Publishing and written by Brett Lantz. This book will help you solve real-world problems with R and Machine learning.
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2 Nov 2019
@Abdul Azeez Thekkekandy
This article describes how AI can be utilized to make a better team strategy from Manager (or Team Coach) in a live soccer game by utilizing SAP HANA and Amazon Sagemaker capabilities together.
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1 Nov 2019
Joel Ivory Johnson
An idea for collecting collecting vehicle sensor and other information and using machine learning on AWS to predict and diagnose vehicle problems before they become serious.
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30 Oct 2019
DaveNoderer
Recommendation System for wholesale automotive sales
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30 Oct 2019
Wayne Applebaum
Discussion of the issues of identifying adverse drug effects and how machine learn and big data techniques can solve for them.
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16 Sep 2019
syed shanu
Introduction to Machine Learning and ML.NET (Machine Learning.NET)
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26 Aug 2019
Thomas Weller
Demonstrates how to run Python scripts from C#
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12 Aug 2019
Sau002
How to create C# applications using TensorFlowSharp
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23 Jul 2019
Packt Publishing
In this article, we will be covering the following topics: When to use regression and classification, how to implement regression and classification using Go machine learning libraries, how to measure the performance of an algorithm.
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24 Jun 2019
Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.
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17 Jun 2019
Ryukkkk
Easy to implement machine learning
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3 Jun 2019
Ryukkkk
Easy to implement machine learning
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28 May 2019
Ryukkkk
Easy to implement machine learning
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28 May 2019
Akhil Mittal
This articleis a complete end to end tutorial that will explain the concept of facerecognition and face detection using modern AI based Azure cognitive servicei.e. Azure’s Face API service.
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20 May 2019
Ryukkkk
Easy to implement machine learning
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20 May 2019
Ryukkkk
Easy to implement machine learning
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12 May 2019
Ryukkkk
Easy to implement machine learning
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5 May 2019
Ryukkkk
Easy to implement machine learning
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28 Apr 2019
Phil Hopley
In this article, we will add AI to an existing ROS (Robot Operating System) House Bot.
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21 Apr 2019
Coding Notes
Diary of learning Machine Learning and TensorFlow
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15 Apr 2019
Afzaal Ahmad Zeeshan
In this article, I will demonstrate how to integrate the Cognitive Services SDKs in a .NET Core based application and explore how real-world scenarios can be tackled using ML services offered by Microsoft.
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15 Apr 2019
Afzaal Ahmad Zeeshan
In this article, I will demonstrate how to integrate the Cognitive Services SDKs in a .NET Core based application and explore how real-world scenarios can be tackled using ML services offered by Microsoft.
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13 Apr 2019
George Swan
An example of how the temporal difference algorithm can be used to teach a machine to become invincible at Tic Tac Toe in under a minute
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12 Apr 2019
MehreenTahir
In this article, we’ll look at some advantages of serverless computing and then dig into a real-world example using the Microsoft Azure Functions service to build and deploy a sample ML inferencing function.
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4 Apr 2019
Apriorit Inc, Semyon Boyko
Find out an easy way to use the pretrained Inception V3 neural network for video classification.
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3 Apr 2019
Mahsa Hassankashi
Best practice for learning Basic of Machine Learning and Gradient Descent based on Linear Regression. This article will explain step by step computational matters.
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3 Apr 2019
Mahsa Hassankashi
This article provides python code for random forest, one of the popular machine learning algorithms in an easy and simple way.
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3 Apr 2019
Mahsa Hassankashi
This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.
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3 Apr 2019
Mahsa Hassankashi
Deep learning convolutional neural network by tensorflow python, complete and easy understanding
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3 Apr 2019
Mahsa Hassankashi
It is almost everything about big data. This article explain practical example how to process big data (>peta byte = 10^15 byte) by using hadoop with multiple cluster definition by spark and compute heavy calculations by the aid of tensorflow libraries in python.
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11 Mar 2019
Coding Notes
An introduction to Infer.NET
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28 Feb 2019
Gaston Verelst
This article discusses how F# is a great language to use to implement algorithms such of k-means because of its conciseness, type inference, and immutability.
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18 Feb 2019
Apriorit Inc, ruksovdev
A detailed description of an FPGA-specific framework called ISE Design Suite, and the main steps you need to take in order to create a VGA driver using FPGA
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25 Jan 2019
Philipp_Engelmann
Competing on kaggle.com for the first time
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22 Jan 2019
KristianEkman
A cell by cell walkthrough of the maths of a Neural network
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21 Jan 2019
Adrian Pirvu
A closer look into differences between natural nervous systems and artificial neural networks
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20 Dec 2018
Andrew Kirillov
The article demonstrates usage of ANNT library for creating recurrent ANNs and applying them to different tasks.
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15 Dec 2018
Dmitriy Gakh
An introduction to Genetic Algorithms with brief reference to biology and example of finding one solution for complex mathematical equation
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14 Dec 2018
Philipp_Engelmann
Simple Linear Regression from scratch in Rust
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14 Dec 2018
Dmitriy Gakh
The perspectives of creating bots that write programs with two simple examples.
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10 Dec 2018
Apriorit Inc, Vadym Zhernovyi
The experience of improving Mask R-CNN performance six to ten times by applying TensorRT
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25 Nov 2018
Coding Notes
An introduction to the SVM and the simplified SMO algorithm
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22 Nov 2018
Philipp_Engelmann
How to create a Turing machine in Python - Part 2
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3 Nov 2018
Philipp_Engelmann
In this series, I want to show you how to create a simple console-based Turing machine in Python. You can check out the full source code on https://github.com/phillikus/turing_machine. In this part, I will explain the fundamental theory behind Turing machines and set up the project based on that.
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1 Nov 2018
Bahrudin Hrnjica
Export options in ANNdotNET
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31 Oct 2018
syed shanu
In this article, we will see how to work on Clustering model for predicting the Mobile used by model, Sex, before 2010 and After 2010 using the Clustering model with ML.NET.
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28 Oct 2018
Andrew Kirillov
The article demonstrates usage of ANNT library for creating convolutional ANNs and applying them to image classification tasks.
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23 Oct 2018
Carlos Conceição
Machine learning road to disappointment
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14 Oct 2018
Bahrudin Hrnjica
ANNdotNET v1.0 has been released
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1 Oct 2018
asiwel
How to Deploy Trained Models Concurrently
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28 Sep 2018
Andrew Kirillov
The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.
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21 Sep 2018
Packt Publishing
Excerpt from the book Mastering Machine Learning for Penetration Testing by Chiheb Chebbi
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3 Sep 2018
asiwel
Bezier Curve Classification Training and Validation Models using CNTK and ALGLIB
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22 Aug 2018
asiwel
Bezier Curve Classification Training And Validation Models Using ALGLIB
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20 Aug 2018
Bahrudin Hrnjica
Linear regression with CNTK and C#
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13 Aug 2018
syed shanu
In this article, we will see how to develop our first ML.Net application to predict the Item stock quantity.
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8 Aug 2018
asiwel
Data modelling and visualization using longitudinal Bezier curves
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18 Jun 2018
Jesús Utrera
Third article of a series of articles introducing deep learning coding in Python and Keras framework
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18 Jun 2018
Jesús Utrera
Second article of a series of articles introducing deep learning coding in Python and Keras framework
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26 Apr 2018
Mahsa Hassankashi
Best practice for opinion and Text Mining based on Naïve Bayesian Classifier.
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22 Mar 2018
Scott Clayton
Build a recommendation system using collaborative filtering and matrix factorization.
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12 Mar 2018
Peter Leow
Design and implement a simple AI agent that can learn and fight the relentless spam plague.
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3 Mar 2018
sjb_strat
Use machine learning to determine the programming language of text
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3 Mar 2018
sjb_strat
Create a Spam Filter Using Machine Learning
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3 Mar 2018
Thomas Daniels
This article describes how to use a neural network to recognize programming languages, as an entry for CodeProject's Machine Learning and Artificial Intelligence Challenge.
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3 Mar 2018
Vince Chan
A walkthrough of common machine learning tasks - by building a Naive Bayes Spam Classifier using python and scikit-learn
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3 Mar 2018
Omar Gameel Salem
Using Collaborative Filtering to find people who share tastes, and for making automatic recommendations based on things that other people like.
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1 Mar 2018
Scott Clayton
Detect the programming language of a code snippet using neural networks in Azure ML Studio
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12 Feb 2018
Scott Clayton
Train a binary classifier in Azure and then use it in a C# application.
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6 Feb 2018
raddevus
Entry in the Artificial Intelligence and Machine Learning Contest. Here's how I learned / guessed how to find spam.
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17 Dec 2017
Vladimir Dorokhov
This article is about building simple machine learning service using ASP.NET Core, Tensorflow and Azure Cloud
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1 Dec 2017
Dmitrii Nemtsov
A way to build a finite-state machine identifying predefined sequences in a stream of characters.
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27 Nov 2017
Jesse Casman
Do developers really need to pay attention to chatbots in a fairly small market of just over a billion dollars?
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21 Nov 2017
Pete Garcin
Exploring how to take one of the pre-trained models for TensorFlow and set it up to be executed in Go - Specifically, detecting multiple objects within any image
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29 Sep 2017
Gamil Yassin
This is a series of articles demonstrating .NET AI library from scratch
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12 Sep 2017
The Zakies
question answer chatbot using natural language parsing and web scrapping
29 Aug 2017
Intel® Nervana™ AI Academy
This article aims to explore what happens when Intel solutions support functional and logic programming languages that are regularly used for AI.
14 Aug 2017
Intel Corporation
In this article, we discuss our teachings about data science in a series of steps so that any product manager or business manager interested in exploring this science will be able take their first step toward becoming a data scientist or at least develop a deeper understanding of this science.
14 Aug 2017
Intel Corporation
Intel is uniquely positioned for AI development—the Intel’s AI Ecosystem offers solutions for all aspects of AI by providing a unified front end for a variety of backend technologies, from hardware to edge devices.
14 Aug 2017
Intel Corporation
There are many techniques to predict the stock price variations, but in this project, New York Times’ news articles headlines is used to predict the change in stock prices.
14 Aug 2017
Intel Corporation
Intel® Software Innovator Joshua Montgomery, Karl Fezer, and Steve Penrod of the Mycroft team let me pick their brains to learn a bit more about Mycroft.
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14 Jun 2017
Andy Allinger
Introduces data clustering and the k-means++ algorithm
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5 Jun 2017
Mahsa Hassankashi
phenomenon prediction and simulation by Markov Chain Mont Carlo
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4 Jun 2017
Akhil Mittal
This is the second article of the series and will largely focus on machine learning processes and scenarios.
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1 Jun 2017
Intel Corporation
This paper introduces Intel software tools recently made available to accelerate deep learning inference in edge devices (such as smart cameras, robotics, autonomous vehicles, etc.) incorporating Intel® Processor Graphics solutions across the spectrum of Intel SOCs.
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1 Jun 2017
Intel Corporation
To make it easier to deploy BigDL, we created a “Deploy to Azure” button on top of the Linux (Ubuntu) edition of the Data Science Virtual Machine (DSVM)
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1 Jun 2017
Intel Corporation
This article provides an overview of recent enhancements available in the BigDL 0.1.0 release (as well as in the upcoming 0.1.1 release)
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1 Jun 2017
Intel Corporation
This paper shows how the python API of the Intel® Data Analytics Acceleration Library (Intel® DAAL) tool works. First, we explain how to manipulate data using the pyDAAL programming interface and then show how to integrate it with python data manipulation/math APIs.
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1 Jun 2017
Intel Corporation
Artificial intelligence holds greater promise in transforming clinical research.
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1 Jun 2017
Intel Corporation
This paper introduces the Artificial Intelligence (AI) community to TensorFlow optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based platforms.
26 May 2017
Intel Corporation
In this article, we will talk about criteria you can use to select correct algorithms based on two real-world machine learning problems that were taken from the well-known Kaggle platform used for predictive modeling and from analytics competitions where data miners compete to produce the best model
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24 May 2017
Akhil Mittal
In this and the following articles on Machine Learning to figure out whatMachine Learning is and what can be achieved with it
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24 May 2017
mohammad farahi
English Number recognition with Multi Layer Perceptron Neural Network (MLP)
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4 May 2017
Intel Corporation
Theano is a Python library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays (numpy.ndarray)
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4 May 2017
Intel Corporation
This article will go over some basics of AI, and outline some tools and resources that may help.
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3 May 2017
Intel Corporation
MXNet is an open-source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices, from cloud infrastructure to mobile devices.
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3 May 2017
Intel Corporation
In this blog post, we highlight one particular class of low precision networks named binarized neural networks (BNNs), the fundamental concepts underlying this class, and introduce a Neon CPU and GPU implementation.
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3 May 2017
Intel Corporation
Nervana is currently developing the Nervana Engine, an application specific integrated circuit (ASIC) that is custom-designed and optimized for deep learning.
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19 Apr 2017
Intel Corporation
In Part 2 we will explore how to configure an integrated development environment (IDE) to build the C++ code example, and provide a code walkthrough based on the AlexNet deep learning topology.
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19 Apr 2017
Intel Corporation
In this post we show how to set up a production-ready machine learning workflow with Intel® Nervana™ technology, neon, and Pachyderm.
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19 Apr 2017
Intel Corporation
This article describes different methods to detect outliers in the data and how the Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize outlier detection when running it on systems equipped with Intel® Xeon® processors.
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19 Apr 2017
Intel Corporation
The Developer's Introduction to Intel MKL-DNN tutorial series examines Intel MKL-DNN from a developer’s perspective. Part 1 identifies informative resources and gives detailed instructions on how to install and build the library components.
12 Apr 2017
Intel Corporation
This article describes a common type of regression analysis called linear regression and how the Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize this algorithm when running it on systems equipped with Intel® Xeon® processors.
12 Apr 2017
Intel Corporation
Today we’ll take a close look at exactly how retailers are using machine learning technologies to maximize their business. To do so, we’ll talk about the application programming interface (API). If you have a technical background, chances are that you might be familiar with and using this important
12 Apr 2017
Intel Corporation
Based on the topics covered and the examples cited in this paper, hopefully you are convinced that the technology advancements, especially those emulating the human brain and eye, are evolving at a fast pace and may soon replace the human eye.
12 Apr 2017
Intel Corporation
In this blog post we will explain transfer learning and some of its applications, explain how neon can be used for transfer learning, walk through example code that uses neon for transferring a pre-trained model to a new dataset, and discuss the merits of transfer learning with some results
12 Apr 2017
Intel Corporation
Intel’s new Deep Learning tools (with the upcoming integration of Nervana’s cloud stack) are designed to hide/reduce the complexity of strong scaling time-to-train and model deployment tradeoffs on resource-constrained edge devices without compromising the performance need.
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26 Mar 2017
Ganesan Senthilvel
An interesting article on Artificial Intelligence Chat Ro(Bot) Application development
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14 Feb 2017
Alibaba Cloud
This post features a basic introduction to machine learning (ML). You don’t need any prior knowledge about ML to get the best out of this article. Before getting started, let’s address this question: "Is ML so important that I really need to read this post?"
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13 Feb 2017
Alibaba Cloud
In this post, we learn about algorithms that help implement ML functions.
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18 Jan 2017
Alibaba Cloud
This post features a basic introduction to Machine Learning. This post on Machine Learning will not only help you to understand the latest trends in the Internet industry, but increase your understanding of the technology that plays a major role in many services that make our lives easier.
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26 Dec 2016
Fernando de Oliveira [MCP]
What if you could predict data using a cloud-based environment? You can do it with Azure Machine Learning.
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19 Dec 2016
Intel Corporation
Now that the eight-week Intel® Ultimate Coder Challenge for IoT is complete, teams continue developing and expanding their projects into the commercial sector.
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19 Dec 2016
petrostherock
Machine Learning. What languages come to mind? R? Python? Matlab? Bet you didn't think Visual Basic.
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30 Nov 2016
Dino Konstantopoulos
Running Theano with an Nvidia 1070 GPU on Windows 10, with CUDA 8 and Visual Studio 2015
16 Nov 2016
Intel Corporation
This project describes how to recognize certain types of human physical activities using acceleration data generated from the ADXL345 accelerometer connected to the Intel® Edison board.
3 Nov 2016
Intel Corporation
To help innovators tackle the complexities of machine learning, we are making performance optimizations available to developers through familiar Intel® software tools, specifically through the Intel® Data Analytics Acceleration Library (Intel® DAAL) and enhancements to the Intel® Math Kernel Library
3 Nov 2016
Intel Corporation
Get Results with the Intel® Data Analytics Acceleration Library and the Latest Intel® Xeon Phi™ Processor
3 Nov 2016
Intel Corporation
Exploring Intel® Data Analytics Acceleration Library C++ Coding for Handwritten Digit Recognition
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22 Oct 2016
Mostafa Eissa
10,000 foot view of machine learning
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21 Oct 2016
Intel Corporation
The Intel® Joule™ module is the newest addition to a line of powerful, multi-purpose development boards from Intel®
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21 Oct 2016
Intel Corporation
Microsoft Azure collaborates with Intel IoT® Technologies to provide developers with a full set of development tools – from the edge to the cloud.
23 Sep 2016
Lee Stott
The Microsoft Data Science Virtual Machine jump starts your analytics project. It enables you to work on tasks in a variety of languages including R, Python, SQL, and C#.
20 Sep 2016
Yuri Diogenes
This article explores how the Microsoft Azure IoT Suite provides a secure and private Internet of Things cloud solution.
14 Sep 2016
Mike Lanzetta
In this post, I'll walk you through how to get one of the most popular toolkits up and running on Windows, and run through and explain some fun examples.
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9 Sep 2016
Intel Corporation
This shop-floor equipment activity monitor application is part of a series of how-to Intel Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
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9 Sep 2016
Intel Corporation
This home fall tracker application is part of a series of how-to Intel® Internet of Things (IoT) code sample exercises using the Intel IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
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9 Sep 2016
Intel Corporation
This guide describes the implementation of an industrial use case using Intel® IoT Gateway and the IBM Watson IoT Platform running on IBM Bluemix.
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28 Aug 2016
Rodrigo Costa Camargos
This article presents how to implement a well-known agglomerative clustering algorithm in C#.
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23 Aug 2016
Florian Rappl
This article describes the most important details of creating a useful bot using the Microsoft Bot Framework.
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19 Aug 2016
Intel Corporation
This project describes how to recognize certain types of human physical activities using acceleration data generated from the ADXL345 accelerometer connected to the Intel® Edison board.
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7 Aug 2016
Grasshopper.iics, Moumita Das
An assistive technology initiative for patients with upper body disability
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7 Aug 2016
Grasshopper.iics
Human Activity tracking and aggregation at the edge with Activity based climate control
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6 Aug 2016
Grasshopper.iics, Moumita Das
A complete Node-Red based suite for home automation, remote IoT based home control and Security System
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6 Aug 2016
Grasshopper.iics, Moumita Das
Agricultural field monitoring and control can also possible using IoT sensor network
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6 Aug 2016
Grasshopper.iics, Abhishek Nandy, Moumita Das
Industrial IoT time series data collection with GE Predix time series ingestion and data streaming
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14 Jul 2016
dcmuggins
Bubble Sort is great...and terrible at the same time.
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20 Jun 2016
Intel Corporation
This line following robot application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
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20 Jun 2016
Intel Corporation
When you connect Internet of Things (IoT) devices (devices that support Intel microcontrollers such as the Intel® Edison board, Intel® Curie™ Compute Module, and Intel® IoT gateways) to the IBM Watson* IoT Platform, you can rapidly build IoT apps that realize your IoT use case.
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20 Jun 2016
Intel Corporation
This article provides general guidelines for connecting any Intel Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers like the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel® IoT Gateways to the Microsoft Azure IoT Suite.
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20 Jun 2016
Intel Corporation
This article provides general guidelines for connecting any Intel® Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers, such as the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel gateways to the Amazon Web Servives (AWS) IoT platform.
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20 Jun 2016
Intel Corporation
Before you embark on a new Internet of Things project, you should consider which communication patterns are best suited to it.
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6 Jun 2016
Clinton Sheppard
A hands-on, step-by-step introduction to machine learning with genetic algorithms using Python.
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1 Jun 2016
Android on Intel
Intel® System Studio 2017 Beta has been released. This is the Beta program page which guides you further on Intel® System Studio 2017 Beta new features and enhanced usability experience.
17 May 2016
Intel Corporation
This smart doorbell application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
17 May 2016
Intel Corporation
This smart alarm clock application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
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9 May 2016
Alexandr Surkov
Principles of video analysis
18 Apr 2016
Intel Corporation
This access control system application is part of a series of how-to Intel® IoT Technology code sample exercises using theIntel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
18 Apr 2016
Intel Corporation
This automatic watering system application is part of a series of how-to Intel IoT code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
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8 Apr 2016
King Coffee
Sample code for OpenCvSharp 3 quick start
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4 Apr 2016
Mr. xieguigang 谢桂纲
R API for drawing venn diagram in VisualBasic
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28 Mar 2016
Mr. xieguigang 谢桂纲
machine playing snake game
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20 Jan 2016
Sacha Barber
Looking at Spark/Cassandra working together
19 Jan 2016
Intel Corporation
This smart stove top application is part of a series of how-to Intel IoT code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
13 Nov 2015
Intel Corporation
A complete list of these JavaScript code sample titles is provided below along with their links to instructions and code.
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1 Sep 2015
Sacha Barber
An introductory article on Apache Spark, with a demo app
27 Jul 2015
Android on Intel
In this article I will explain what is DNN and how the Intel® SSSE3 instruction set helps to accelerate DNN calculation progress.
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20 Jul 2015
Ashkan Pourghasem
Hands on tutorial of implementing batch gradient descent to solve a linear regression problem in Matlab
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6 Jul 2015
Matteo Manferdini
A guide on how to be on top of iOS development
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31 Mar 2015
Sudhir Kshirsagar
The availability of low cost sensors for environmental monitoring coupled with the capabilities of the Microsoft Cloud provides a set of enormous opportunities in building a solid infrastructure for smart cities.
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31 Mar 2015
Prakash SNP
This article shows how to build an Azure IoT Solution for water utilities Industry
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30 Mar 2015
Florian Rappl, Niki Kilbertus
Using Microsoft Azure to add advanced machine learning capabilities with connected IoT devices, which monitor activities of a baby and his or her environment.
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25 Mar 2015
Glenn Vassallo
An end to end IoT system utilising Microsoft Azure Cloud Technology and an embedded device, the Texas Instruments CC3200 LaunchPad (Single Chip Wi-Fi MCU).
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22 Mar 2015
Aby Mammen Mathew
IoT devices needs the capability to augment the environment around them, even when sensors utilized by them break down
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25 Feb 2015
Todd Christell, Canin Christell
Creating a Microwave Oven IoT Application
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30 Jan 2015
Jesús Utrera
In this article we will train the machine to compare strings using logistic regression applied to the result of using Levenshtein algorithms (adapted) and Jaro-Winkler.
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2 Dec 2014
César de Souza
A description of how it was possible to achieve real-time face detection with some clever ideas back in 2001