Building a Self-Racing Race Car – The Journey Begins

Matthew_v1

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So today I have decided to actually begin a write up on where I’m headed.  Its taken a long while to come up with what my next adventure after food trucks was going to be, especially with all of the things you can do with embedded technologies and machine learning.  So here it is, a self driving race car.

In this article I aim to lay out the high level plan of attack for what my team and I are building and some of the direction on where we are headed.

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Operationalizing SKLearn with Azure Machine Learning

web_servic-ified

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So I just completed an incredible project with Brain Thermal Tunnel Genix, where I learned so much about pattern recognition, machine learning and taking research and algorithms and pushing those into a production environment where it can be integrated into a real product.  Today’s article takes those lessons and provides a sample on how to perform complex modelling and operationalize it in the cloud.  The accompanying Gallery Example can be found here.

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Arduino + Reinforcement Learning = Autonomous Robot

Herby_V1

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So there are a ton of articles out there on the theory of Reinforcement Learning, but very few with an actual application.  I watched a few lectures from Berkley, and read a few articles by NVidia and thought, “Well, lets just give this a shot”.  8 hours later, this is what I had.

Herby_V1

Herby V1 simply learns to go forward as much as possible while avoiding obstacles.

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The Cognitive Revolution

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So here is a pretty raw blog article; not unlike most of my articles.  The cognitive revolution.  I’m going to coin this term today.  What the heck is this thing?  What does it mean for you?  What does it mean for me?  Where did it come from?  What is it?  These are questions I aim to answer in this blog article.

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Standardize Continuous Data Shape for Neural Networks

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So this is an interesting problem.  You are collecting data from somewhere and you want to feed it into a neural network for classification.  There is one main problem with this.  The shape of the data!  Neural networks and really just anything require specifically shaped data, you can’t just like give it something of ambiguous size.  There are tons of papers out there on dimensionality reduction, but nothing on dimensionality reduction to a specified size.  This article explains my approach.

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Becoming a Functional Data Scientist

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So today, I was asked to put some thought into what we should focus our entry level data scientists on in terms of tech skills.  After I put a bunch of thought into it, I ended up coming up with this.  I decided that the most important aspect of this was a few items fold

  1. Don’t overload them
  2. Can deliver to production where the target can be anything, including IoT.
  3. They will not be concerned with building front ends.

I have to say, the result greatly surprised me.

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Microsoft Tech and Robotics

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This article is a high level discussion on where you might use various Microsoft Technologies in the field of robotics.  I will begin with a side pet project I’m kicking off to get more familiar with some cool tools and tech I’ve lately discovered so I can hopefully get assigned to some really cool projects at work, including drones.

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K-Means under the hood with Python

plot_6

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This article is meant to explain how the K-Means Clustering algorithm works while simultaneously learning a little Python.

What is K-Means?

K-Means Clustering is an unsupervised learning algorithm that tells you how similar observations are by putting them into groups or “clusters”.  K-Means is often used as a discovery step on new data to discover what various categories might be and then apply something such as a k-nearest-neighbor as a classifier to it after understanding the centroid labels.  Where a centroid is the center of a “cluster” or group.

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SQL Saturday 524 Slides – Analytical Computing – Device to Cloud and Back

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Here you can find the slide deck for my talk for SQL Saturday #524 in South Florida.  I hope you find this useful, but it should be far more useful if you attend in person.  This talk lays the foundation for building and understanding analytical computing for cloud and devices as well as how they work together.

https://drcdata.blob.core.windows.net/slidedecks/Analytics_Device_To_Cloud_And_Back.pptx