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Paul langdon

Paul L. added photos to project Edge Computer Vision on Intel NUC

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Edge Computer Vision on Intel NUC

Didn't get your hands on an Amazon DeepLens at re:Invent? Build your own and get started building your own Machine Learning developer toolkit with Intel NUC and start exploring the basics of deep learning.

This project will walk you through the setup of the hardware and the installation of your first training model to implement computer vision at the edge.

We we use AWS SageMaker, Apache MXNet, and Jupyter Notebook to set up our first project on your own hardware.

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Paul L. created project Edge Computer Vision on Intel NUC

Medium f57aabd0 67c3 4ae5 845b c8dcc24327be

Edge Computer Vision on Intel NUC

Didn't get your hands on an Amazon DeepLens at re:Invent? Build your own and get started building your own Machine Learning developer toolkit with Intel NUC and start exploring the basics of deep learning.

This project will walk you through the setup of the hardware and the installation of your first training model to implement computer vision at the edge.

We we use AWS SageMaker, Apache MXNet, and Jupyter Notebook to set up our first project on your own hardware.

Paul langdon

Paul L. added photos to project DeepMirror - SmartHome Gateway

Medium e26b062e 9c02 495c 880d 9c67fa2245f8

DeepMirror - SmartHome Gateway

The MagicMirror project was originally developed for RaspPi, it has taken off with community developed modules for many smart home and information services. The Intel NUC serving as gateway allows for the full extension of AI and Machine Learning.

- Camera to do face recognition and context switching - (Cloud trained model executes local - can be accelerated )
(i.e. when I walk up to the mirror it recognizes me, presents my calendar and email vs. when another user walk up)
- Voice Recognition/Control - Integrating voice with SDKs (Google, Amazon and Mycroft)
- Full Port of Amazon's Deep Lens (https://aws.amazon.com/deeplens/) funning on Intel NUC
- Smart Home Power Metering - IoT Hardware + anomaly detection using ML
- HDMI video output to mirror for heads up display
-------------------

Highlights:

Demo of Deep Learning - cloud trained model using Jupyter notebooks and Amazon's Sagemaker. Cloud trained models execute locally on Ubuntu Linux on NUC gateway.

Node.js for UI

Module framework

---------

Git:
https://github.com/plangdon/OnTheWall

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Paul L. created project IoT Analytics Gateway

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IoT Analytics Gateway

Creation of a scaleable and efficient Analytics Gateway to collect anonymous usage data was achieved leveraging a "Serverless" Architecture. The "Serverless" Framework allows the construction auto-scaling, event driven components deployable to many cloud platforms such as Amazon Web Services, Azure and Google Cloud Platform or as the business case requires, deploying as easily to your own private cloud (Intel Private Cloud). Currently servicing sensor and usage data to over 20,000 live connected IoT devices deployed across the U.S., we are able to collect real-time, anonymous statistics for only pennies per device over the service life of the device.

Extremely Low latency (<100ms) and minimal downtime from connectivity disruption is achieved from this service model.

Exploration of usage of Analytics data with leading Machine Learning platforms: Caffe2 (on AWS), Apache Spark BigDL, Cloud AI (Google) & Watson (IBM).

Topics explored: * Serverless - https://serverless.com/ * Caffe2 - https://caffe2.ai/ * Google Cloud AI - https://cloud.google.com/products/machine-learning/ * Apache Spark BigDL - https://software.intel.com/en-us/articles/bigdl-distributed-deep-learning-on-apache-spark * IBM Watson Machine Learning - https://datascience.ibm.com/features#machinelearning * Intel Private Cloud - https://www.intel.com/content/www/us/en/cloud-computing/private-cloud-solutions.html

Medium paul langdon

Paul L. created project DeepMirror - SmartHome Gateway

Medium e26b062e 9c02 495c 880d 9c67fa2245f8

DeepMirror - SmartHome Gateway

The MagicMirror project was originally developed for RaspPi, it has taken off with community developed modules for many smart home and information services. The Intel NUC serving as gateway allows for the full extension of AI and Machine Learning.

- Camera to do face recognition and context switching - (Cloud trained model executes local - can be accelerated ) 
         (i.e. when I walk up to the mirror it recognizes me, presents my calendar and email vs. when another user walk up) 
-  Voice Recognition/Control  - Integrating voice with SDKs (Google, Amazon and Mycroft)
-  Full Port of Amazon's Deep Lens (https://aws.amazon.com/deeplens/) funning on Intel NUC
-  Smart Home Power Metering - IoT Hardware + anomaly detection using ML
-  HDMI video output to mirror for heads up display 

Highlights:

Demo of Deep Learning - cloud trained model using Jupyter notebooks and Amazon's Sagemaker. Cloud trained models execute locally on Ubuntu Linux on NUC gateway.

Node.js for UI

Module framework


Git: https://github.com/plangdon/OnTheWall

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Paul L. updated status

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Paul Langdon

MagicMirror+++ for Intel Joule

Adding Face Recognition/Voice Recognition/Voice Control using RealSense, Amazon Voice and wit.ai to make a full smart home AI experience that hides as a mirror until you call it into action.

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