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.
This is a high level article geared for general consumption of the normal individual! I’ve been thinking about types of customer engagements I have been doing lately and decided to break it down into a series of categorical engagements. There are 4 categories of engagements: Descriptive, Predictive, Prescriptive and Actuated Analytics engagements.
So I wrote an article earlier “Linear Regression From Scratch”. Many folks have pointed out that this is in fact not the optimal approach. Now being the perfectionist I decided to re-implement. Not to mention it works great in my own libraries. The following article discussing converting the original code into code that uses linear algebra. Beyond this, it still works in PCL for xamarin, Hoo-Rah Xamarin!
So this article is to help provide some guidance around which programming language to use. Note that this article is specifically geared towards delivering code in which intelligence and information is the soul of the product. In this day and age, that should be every product.
I want to preface this article with a few things
This is an excerpt from a paper I wrote for internal use of my own volition. As this is the case, I was able to remove all confidential information and publish my findings.
I only analyzed F#, C#, R and Python. I know there are more, but I picked the top dogs, but F# had some special circumstances that I felt it belonged.
So I’ve been working on building some interesting visualizations with open data. Today I get to show off a really interesting one, not only will we discuss the visualization in depth, but also dive into how I built it. And here it is, the top 10 bookings in Miami where the legend is in descending order for most common bookings holistically.
Here is a recorded version of an in-person training I have been doing. Enjoy. I end up coming back to this myself even for reference.
This episode is all about performing data manipulation to derive raw insights from your data using the R programming language. Data manipulation is the core to anything and everything you do in business intelligence and machine learning. This episode sets the base for all R based intelligence sessions from here on out.
Ever wonder the difference between R and Microsoft R? Considering learning R as a programming language? You should probably watch this video. It is the first in a 4 part series to give you the jump start you need to becoming a professional data scientist with R.
Project Teddy – Embedded Systems + Big Data with David Crook
Friday, Aug 21, 2015, 6:00 PM
PricewaterhouseCoopers, LLP. 600 Silks Run Suite# 2210 Hallandale Beach, FL
18 ETs Went
Project Teddy is an IoT/Big Data project currently under development by the South Florida Developer Evangelist Team. The goal of PT is to build a teddy bear that you can literally have a normal conversation with. This meetup is to discuss the current progress of project teddy from a technology perspective, how it is built, why it is being built t…