https://www.minimizeuncertainty.com/ Recent content on Uncertainty...Minimized Hugo -- gohugo.io mj514316@domain.com (Michael C Johnson) mj514316@domain.com (Michael C Johnson) Mon, 09 Mar 2020 00:00:00 +0000 https://www.minimizeuncertainty.com/post/my-favorite-data-science-resources/ Mon, 09 Mar 2020 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/my-favorite-data-science-resources/ People often ask me, “what resources do you use to keep on top of machine learning”? I spent some time curating some of my favorite resources and I figured this would be a fine place to share them. But first, there is some bad news. The best resource I know of for staying abreast of developments in the field is Twitter. I know, this is not what you (or I) wanted to hear, but time and time again Twitter has shown me new papers or new findings that have had significant impact on what my team does. https://www.minimizeuncertainty.com/post/distributed-graph-representations-using-the-mueller-report/ Sat, 25 Jan 2020 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/distributed-graph-representations-using-the-mueller-report/ Note: This is part 2 of my series on the Mueller Report. Please take a look at Part 1 if you are interested in how I built the graph. One thing that would be useful when navigating a document (or set of documents) like the Mueller Report is the ability to find things that are ‘like’ other things. For example, if you are trying to follow the thread of a story through the document, you might want to find all the paragraphs that are about similar things to the paragraph you are interested in. https://www.minimizeuncertainty.com/post/graph-visualization-of-the-mueller-report-with-spacy-and-pyvis/ Wed, 19 Jun 2019 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/graph-visualization-of-the-mueller-report-with-spacy-and-pyvis/ One of the most interesting talks I heard at Strata in San Francisco this year was “Towards deep and representation learning for talent search at LinkedIn”. In the talk, Gungor explained how he took advantage of LinkedIn’s economic graph to build a hyper-personalized search engine. Ever since then I’ve had graphs firmly planted in my mind. Not these graphs: Graph More like these: Network Specifically, I’ve been trying to understand how graph network techniques can be applied in various domains, including natural language processing. https://www.minimizeuncertainty.com/post/statistically-verifying-claims-made-in-childrens-stories/ Fri, 25 Jan 2019 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/statistically-verifying-claims-made-in-childrens-stories/ Bedtime has historically been a battle for our family. Kids have this impressive ability to fall asleep when you want them awake and vigorously stay awake when you want them to sleep. To combat the insanity, we read a few books every night before bed. There is a great series of books for young children called “The Magic Tree House”. The series follows two children (Jack and Annie) who transport to other times and places for some mystery or adventure. https://www.minimizeuncertainty.com/post/how-many-is-too-many/ Sat, 19 Jan 2019 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/how-many-is-too-many/ Anyone who has multiple boys in a row at some point asks themselves a question: did I just get ‘lucky’ or are we only able to have boys? As you can see, we certainly asked that question… When we had our third boy in a row I started to wonder: how many children do you have to have of a given sex before you can statistically conclude that there is something other than random chance influencing to the outcome? https://www.minimizeuncertainty.com/post/deep-autoencoder-neural-networks-for-maximal-christmas-decoration-enjoyment/ Wed, 21 Nov 2018 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/post/deep-autoencoder-neural-networks-for-maximal-christmas-decoration-enjoyment/ My wife loves decorations. From Valentines Day to Easter to Thanksgiving, our house is adorned with interesting festive items. Her favorite season by far is Christmas. Every December we drive around trying to find the best Christmas lights. Inevitably, there are a few houses with lights that blink with the music, something I’ve always been fascinated with. Two years ago I embarked on a mission to build my own Christmas Light Show, specifically this is what I had in mind: https://www.minimizeuncertainty.com/page/about/ Mon, 01 Jan 0001 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/page/about/ About me code{white-space: pre;} pre:not([class]) { background-color: white; } if (window.hljs) { hljs.configure({languages: []}); hljs.initHighlightingOnLoad(); if (document.readyState && document.readyState === "complete") { window.setTimeout(function() { hljs.initHighlighting(); }, 0); } } h1 { font-size: 34px; } h1.title { font-size: 38px; } h2 { font-size: 30px; } h3 { font-size: 24px; } h4 { font-size: 18px; } h5 { font-size: 16px; } h6 { font-size: 12px; } . https://www.minimizeuncertainty.com/page/about/ Mon, 01 Jan 0001 00:00:00 +0000 mj514316@domain.com (Michael C Johnson) https://www.minimizeuncertainty.com/page/about/ I am the lead for a growing team of Data Scientists at Lockheed Martin. I have one of the coolest jobs in the world, allowing me to apply deep learning and machine learning algorithms to business problems in a broad variety of domains. I’ve recently been focused on NLP, using CNN and LSTM based deep learning models to build end to end NLP pipelines. I studied physics at The Colorado School of Mines and moved into the field of semiconductor reliability at IBM.