It would appear that making a rolling list of all my old and newer RapidMiner Tutorials would be helpful for readers. It should be noted that these tutorials and videos were made for differnet versions of RapidMiner (version 5 to 7) and may look a bit old and dated BUT they are still relevant to this day. The functionality of RapidMiner is still the same but the internal organization and look will be different.

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 the stream of consciousness from my Working with Instgram API, JSONPath, and RapidMiner post, I started beta testing a new and improved Instagram Hashtag Tool. I’ve even opened it up to a few beta testers (ping me if you want to try it). It uses a RapidMiner Server on the backend to watch a Dropbox folder. Once you put a text file into the ‘In’ folder, it triggers a process and spits back a spreadsheet in the ‘Out’ folder.

This is the forward to an updated ultimate guide 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 in the beginning but with the right tools and attitude, you can ‘huff’ your way into this field.

This is a great video presentation on Fraud Analytics use case with RapidMiner. See my notes below. ##Some key concepts More complex model, the lower the training error but higher test error. Simple models are better, try explaining them to children. Data Scientists understand the technical aspect, need to communicate results with analysts. Sell results to businesses. Tie $ to the results. Speak same language with business. Map performance metrics to business related figures.

Hi friends, I would love it if you signed up for my 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. At the rate I’m sending out newsletters it might be once or twice a year! So completely non-obtrusive and gentle. If you want to sign up for it, you can do so here or below.

This is a great introduction to Deep Learning. I know I learned a few things from Phillip. Some key concepts RapidMiner now can do GPU deep learning. Supports NVIDIA. Easy: Using already loaded Neural Net operators. Harder: Using H20.ai Deep Learning operator. Hardest: Using Keras with RapidMiner. Keras requires more complex setup with RapidMiner. CNN, RNN, LSTM, etc are now available via RapidMiner GUI. Keras supports Tensorflow, CNTK, and Theano. Need Python v3.

Let’s talk Process Mining and Engineering. Why? Because it’s the silver bullet that many Engineering firms are looking for but have never found. Let me explain. I’ve spent years working at small and large Engineering firms and they hardly made any money. Engineering firms are notorious for making 1 to 3% net margin at the end of the day. The joke was that the only reason these firms exist is to keep people employed!

October 2016 Just a quick list of the content I’ve created some place other than this blog. This current list is 100% RapidMiner related but I’d like to branch out into guest posting. If any of my readers would like a guest post on their blog or site from me, then contact me. Tips and Tricks: How to use Python and R with Rapidminer Tips and Tricks: Different Ways to Join Data How to Use Data Science to Predict Qualifed Leads December 2018 I’m happy to announce my very first article went live on the H2O.

Back in middle school we learned about log tables. We learned how to look them up in a table, interpolate them, and then use the result in our equations. Later on they allowed us to use calculators, which made our lives easier and faster. Fast forward many years to a Sunday morning this October. I was at my dining table with my laptop open, fooling with Pandas and iPython Notebooks (aka Juypter).

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.

The image below is my first Raspberry Pi computer.  It's an amazing little thing and I decided to purchase one ($35 USD) so I can connect it to my weather station and upload its data, in 15 minute intervals, to the Internet and my FTP site.  Why?  Well I love data if you haven't figured that out by now, and I want to give back to the community. So far I've installed the Raspbian Linux kernel on a 4GB SD card and got it to recognize and connect an Edimax Wifi dongle(sp).

Today’s guest post about an awesome new plugin for Rapidminer, is from Milan Vukicevic. Although I walked in at the very end of his presentation at RCOMM 2010, I sat down with Milan on my last day and he gave me a personal demo of WhiBo. The applications I see from this plugin, as it relates to the financial world, is its ability to build algorithms on new data, find patterns, and tweak parameters that were never possible before.

Wow, I’m happy to announce that today is the first of a two part guest post series. Today’s guest post is by Marin Matijas, who gave a presentation at RCOMM 2010 about Short Term Load Forecasting using Support Vector Machines (SVM). I asked Marin to elaborate a little about his use of the Radial Bias Function (RBF) in Rapidminer’s SVM operator and here’s what he had to say! I did edit the post a bit for readability.