There was a question from the RapidMiner Community on how to make a word clouds in RapidMiner using R. It’s really easy. First, you’ll need to make sure you have the Execute R extension installed and configured, then you need to download the “wordcloud” and “RColorBrewer” packages from R Cran Repository. ...

While VC’s are a necessary part of growing a startup, they can kill it too. I’ve seen this happen too many times where the VC’s kill the goose that laid the golden egg. They’re so driven by financial goals that they interfere with great startups that just need a bit more time to ‘gel.’ A recent study commissioned by Eric Paley at Founder Collective found that by pressuring companies to scale prematurely, venture capitalists are indirectly responsible for more startup deaths than founder infighting, technical debt and slow customer adoption — combined. via Techcrunch ...

I’m really liking the overhaul of the old Value Series extension. RapidMiner has been building a new Time Series extension that started with the great ARIMA operator. Now they’re adding new Windowing and Sliding Window operators. My notes below the video. Notes: New time series datasets added to updated Time Series extension (gas station prices) Plus three more sample data templates New Windowing operator, easier to use parameters. New Indices parameter / New Horizon Width and Horizon Offset New Process Windows operator. It’s like a Loop for Time Series data - NICE! New Forecast Validation. Appears to be a redo the old Sliding Window Validation operator In the Testing side of the Forecast Validation operator, you don’t need to use Apply Model Difference between Forecast Validation (FV) and Cross Validation (CV) operator is that the model delivered by FV is always the LAST model that was trained, not like CV that trains over the entire data in the final iteration

I completely fail in this live stream and it’s hilarious. Before I crash and burn, I do talk about how to upsample, downsample, and balance data! Come check it out.

My latest livestream. In this episode I continue with the Word2Vec process and build a synomym stemming dictionary. Then I talk about how to do time series in RapidMiner. I explain the Windowing operator, the Sliding Window Validation operator and show how to insert a bit of R code to deseason a time series. I’m going to change the time for the next Live Stream. Stay tuned for next livestream on 5/25/18 at 12PM EDT. ...

Description: RapidMiner Livestream. I share some tips and tricks on how to use RapidMiner. My latest livestream. In this episode I show you how to share processes in XML and RMP formats, how to open Views, install Wordnet and configure it properly. Then we try out @mschmitz_’s Word2Vec process and realize that it’ll train for over 30 minutes. Stay tuned for next livestream 5/18/18 at 8AM EDT. ...

This article cracks me up. Let’s be real: tensorflow is more like 5 frameworks awkwardly fused together than a single framework - there are so many ways to do 2d convolutions, in tf.layers, the “Dense” layer is different than the “dense” one - how are they different? only one way to find out! There are a ton of tutorials on the internet for doing the same thing in tensorflow but pretty much every one is different because there are so many damn APIs and they’re all incompatible with each other. ...

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 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. Will you be a Data Scientist after reading these series of posts? Of course not, but you’ll have a framework to move forward or at the least, have a better understanding what we do. ...

Coming on the heels of “I told you so,” China is using facial recognition to make sure you’re a good Chinese citizen. Authorities in Shenzhen, China, have set up artificial intelligence-powered CCTV cameras to scan the faces of those who jaywalk at major intersections and display their identities on large LED screens for all to see. If that isn’t punishment enough, plans are now in place to link the current system with cellular technology, so offenders will also be sent a text message with a fine as soon as they are caught crossing the road against traffic lights. via Newsweek ...