About

blog3.pngI add things to this site pretty much every week, so to help you navigate all the articles, I’ve set up this handy guide. You can bookmark this article, and I’ll make sure I keep it up to date as I add new Data Science Notebook entries. In essence, I’m creating a book as I go, so it needs a Table of Contents. (this is that)

 

Learning Data Science

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Prepping for learning Data Science Start here to begin your journey into Data Science. I cover learning to learn, and other education topics for the Data Scientist.
The (Amateur) Data Science Body of Knowledge The general set of knowledge a Data Scientist should have. Think of this as a syllabus.
The Five Minute* Guide to Machine Learning Can you really learn Machine Learning in 5 minutes? Well, sort of.
Learn First or Use First? Should you start learning a tool or process, or should you get some theoretical knowledge first? Turns out, the answer is “yes”!
The Hardest Thing in Data Science It’s math, right? Tell me it’s math. No, it isn’t. The hardest thing in Data Science is asking a good question. This will show you how.
Databas(ics) Surely you know what data is. Well, maybe you don’t (and don’t call me Shirley).
Data Science and the Lytro Camera Instead of ETL, Use ELT – leave the data as it is when you ingress it.
But *Why* Do You Trust Your Data A Data Catalog is probably the best place to start any new Data Science Project.
Can Data Science Cure Creeping Determinism? There are many biases you’ll encounter in Data Science, few as hard to understand and correct as this one. I’ll give you some tools to do that.
The Importance of Unit of Analysis Data Science projects are different than traditional data analysis in a couple of aspects, notably in how you evaluate the base data.

Learning Statistics

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Learning Statistics A survey of free and not so free places to quickly learn statistics. You’ll need a firm understanding of this topic if you’re serious about learning Data Science.
Descriptive Statistics – Initial Evaluation of the Data The first type of statistics – describing a set of data.
Knowing Which Statistical Formula to Use With so many statistical processes and methods out there, which do you choose to solve a given problem? This article shows you how.
Reducing (although sadly not eliminating) bias in sample gathering Bias is the act of non-randomization. It’s impossible to eliminate it, but you can reduce it or account for it.

Tools, Software, and Processes

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The Data Scientist’s Computer You’ll need a system to install software on and use. This article discusses some of the choices you need to make.
CIS – What to use When The Cortana Intelligence Suite contains a wide array of tools you can use in a Data Science project. But which one do you use for a given solution? This article shows you one method of choosing what you need.
Python for the Data Scientist Python started as a simple scripting language, but has grown to be one of the primary languages Data Scientists use in their daily work. This article shows you where to get it and how to get started.
Statistics: Working with R and Revolution Analytics Software R is the language of choice for the Data Scientist, and Revolution Analytics (now Microsoft R Server) fixes it’s major limitations. This article shows you how to install and get started learning R.
R Misteaks – Episode I R is pretty simple to learn, but gets deep quick. And as you start, you’ll make mistakes. I cover a few here along with some fixes.
Occam’s Razor and Data Science Why does Cortana Analytics have so many components? Couldn’t we just do everything in one product? Read more to find out why the simplest answer isn’t always the best…
Is the Microsoft R Client a…client? It seems that some product names don’t accurately describe what they really do – but in some cases, this is necessary. In this post, I’ll cover the different “flavors” of Microsoft R, from the clients to the servers.

Data Visualization

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Data Visualization Basics for Data Scientists A picture is worth a thousand words. But that doesn’t mean you should use a thousand elements in a graphic. Start here to understand more about visualizing data.

The Structure of the Notebook and other Articles

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The “Field Notebook” for Data Science This site is arranged as a Scientific Field Notebook. If you’re not familiar with that format, start here.
Answer a fool, don’t answer a fool An example of Data Science done wrong. A cautionary tale.
I am Data Science, and you can too! (or, Buck is Back) The initial article on this site – explains who I am and why I’m doing this.

5 thoughts on “About”

  1. Hola, Reading a blog is a real pleasure, thanks !

    Liked by 1 person

  2. Why the partial 1885 map of Brevard County Florida at the top of the blog?

    Like

  3. Then we have something in common: Brevard County and old maps. Contact me at my personal email, William@lamartin.com, and I will provide you with a few links to my map work.

    Liked by 1 person

  4. Definitely believe that which you stated. Your favorite reason appeared to
    be on the web the easiest thing to be aware of.

    I say to you, I certainly get annoyed while people think about worries that they juat don’t know about.
    You managed to hitt the nail upon the top and defined out the whole thing without having side effect , people can take a signal.
    Will probably be back to get more. Thanks

    Like

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