Below you will find pages that utilize the taxonomy term “Data Science”
I’m finally getting around to writing Part 2 of Getting Started in Data Science. The first part can be found here. I made suggestions for university students interested in the field of Data Science. I even made a video about it too.
Pick Two, Master One Pick two computer languages and become proficient in one and a master at the other one. Or, pick a platform like H2O-Flow or RapidMiner and a language.
For those that are wondering why I left RapidMiner, my dream job, there are no gory details to share. The simple reason is I got burnt out. My time at RapidMiner was some of the best learning and growth years in my entire professional career. I solved problems, made presentations to C-suite people, and worked with some of the best talent. The flipside of this was that it wasn’t easy and it sure as hell wasn’t a smooth ride.
Continuing my RapidMiner Server series. In this video I show you how to save a RapidMiner Studio process to RapidMiner Server. Then configure RapidMiner Server and a Job Agent to use Python. The result is a productionalization of a simple auto posting Twitter process.
This is an example process of how to use Word2Vec in RapidMiner with the Search Twitter operator. For more information check out this post on the community.
I’ll be going over this in a bit more detail at my next live stream here.
<?xml version="1.0" encoding="UTF-8"?><process version="8.1.001"> <context> <input/> <output/> <macros/> </context> <operator activated="true" class="process" compatibility="8.1.001" expanded="true" name="Process"> <process expanded="true"> <operator activated="true" class="social_media:search_twitter" compatibility="8.1.000" expanded="true" height="68" name="Search Twitter" width="90" x="45" y="34"> <parameter key="connection" value="Twitter - Studio Connection"/> <parameter key="query" value="rapidminer"/> <parameter key="locale" value="en"/> </operator> <operator activated="true" class="select_attributes" compatibility="8.
I had my first YouTube LiveStream on how to use RapidMiner. It’s about 48 minutes long and I do a GUI overview and do some text mining. I even answer a few questions on using PHP and RapidMiner. The audio starts about 3 minutes in.
I’m scheduling the next one tenatively for Friday 5⁄11 at 8 AM EDT (New York time).
This is the forward to an introduction on getting started in data science. I wanted to write a set of ‘getting started’ posts to share with readers on how I became a data scientist at RapidMiner. How I went from a civil engineer with an MBA to working for an amazing startup. Granted, I’m not a classically trained data scientist, I hardly knew how to code but with the right tools and attitude, you can ‘huff’ your way into this field.
Hi friends, I would love it if you signed up for my monthly newsletter. I try not to be obtrusive with it and want to genuinely share valuable information with you. This is a Data Science/Machine Learning related newsletter with a few other random topics related to consulting life.
If you want to sign up for it, you can do so here. I won’t spam or sell your email to a 3rd party.
I’ve been doing a lot more Python hacking, especially around text mining and using the deep learning library Keras and NLTK. Normally I’d do most of my work in RapidMiner but I wanted to do some grunt work and learn something along the way. It was really about educating myself on Recurrent Neural Networks (RNN) and doing it the hard way I guess.
As usually I went to google to do some sleuthing about how to text mine using an LSTM implementation of Keras and boy did I find some goodies.
A few months ago I read about a programmer that automated his job down to the point where the coffee machine would make him lattes! Despite the ethical quandary, I thought it was pretty cool to automate your job with scripts. Then I wondered, was it possible to automate data science? Or at least parts of it? This general question proved to be a rabbit hole of exploration.
StackExchange has an ongoing discussion into another programmer’s automation of his tasks.
This past Friday I resigned from my position as a Civil Engineering Manager at SYSTRA, my employer of the last 6+ years. I did this because an opportunity of a lifetime knocked on my door, an opportunity that will give me a chance to pursue my passion in an exciting and growing field. In short, an opportunity to follow my dreams.
I've accepted a position as a senior consultant at Rapidminer, in their Boston headquarters, and I couldn't be more excited about this.
It’s been 13 years since I first wrote this article and I’m going to update it with what I learned working in the data science and machine learning trenches. A lot of the original 9 steps I posted about below still matter but might operate differently in real-world applications. These are great academic ways to flesh out the problem but in the real world, there’s more stakeholders and other IT related silos that you have to deal with.