Tag: fun

Feed: R-bloggers. Author: R on Will Hipson. Latent Profile Analysis (LPA) tries to identify clusters of individuals (i.e., latent profiles) based on responses to a series of continuous variables (i.e., indicators). LPA assumes that there are unobserved latent profiles that generate patterns of responses on indicator items. Here, I will go through a quick example of LPA to identify groups of people based on their interests/hobbies. The data comes from the Young People Survey, available freely on Kaggle.com. Here’s a sneak peek at what we’re going for: Terminology note: People use the terms clusters, profiles, classes, and groups interchangeably, but ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. Describing the Data Science analytics development process has always been a struggle for me.  The corporate world is full of linear processes.  Major monolithic enterprise applications – ERP, MRP, SFA, CRM systems – have been architected to reduce operational complexity via a series of interlocking, heavily-engineered (and re-engineered) linear processes (though I suspect that anyone who has survived an SAP ERP implementation would take issue with my “reduce operational complexity” statement). The data science development process could not be more different.  The Data Science development process is marked by ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. Today is the first-ever Global Graph Celebration Day! Graph enthusiasts all over the globe are honoring the birthday of Leonhard Euler, the inventor of graph theory, with 60+ events worldwide. As part of today’s graph-inspired festivities commemorating Euler, we have an exciting announcement to share with you.We’re thrilled to announce the availability of the O’Reilly book Graph Algorithms: Practical Examples in Apache Spark & Neo4j – a practical guide to help you get the most out of graph analytics.Until recently, adopting graph analytics required significant expertise and determination – tools and integrations ... Read More

Feed: R-bloggers. Author: Roman Luštrik. Imagine you have a function that only takes one argument, but you would really like to work on a vector of values. A short example on how function Vectorize() can accomplish this. Let’s say we have a data.frame xy data.frame(sample = c("C_pre_sample1", "C_post_sample1", "T_pre_sample2", "T_post_sample2", "NA_pre_sample1"), value = runif(5)) # sample value # 1 C_pre_sample1 0.3048032 # 2 C_post_sample1 0.3487163 # 3 T_pre_sample2 0.3359707 # 4 T_post_sample2 0.6698358 # 5 NA_pre_sample1 0.9490707 and you want to subset only samples that start with C_pre or T_pre. Of course you can construct a nice regular expression, implement ... Read More

Feed: R-bloggers. Author: Daniel Oehm. Every so often a problem arises where it’s appropriate to use gradient descent, and it’s fun (and / or easier) to apply it manually. Recently I’ve applied it optimising a basic recommender system to ‘unsuppressing’ suppressed tabular data. I thought I’d do a series of posts about how I’ve used gradient descent, but figured it was worth while starting with the basics as a primer / refresher. To understand how this works gradient descent is applied we’ll use the classic example, linear regression. A simple linear regression model is of the form     where ... Read More

Feed: MemSQL Blog. Author: Kristi Lewandowski. On November 6, 2018, we made our then-new production product, MemSQL 6.7, free to use, up to certain limits, described below. To date, we’ve had more than 4,500 sign-ups for this version, with numerous individuals and companies using MemSQL to do some amazing things. To quickly recap, with MemSQL any customer can sign up and start using our full featured product, with all enterprise capabilities, including high availability and security, for free. In talking to customers about their experience and what they’ve built, feedback has been astounding, with folks telling us they can’t believe ... Read More

Author: . As the reality of our Sofia office moved from concept (one engineer working from home) to reality (six engineers working together in a real office), it seemed that the time was ripe to have one of our almost-quarterly Engineering Summits in Bulgaria. We still have several open positions there so I felt it was a good opportunity to meet some of our recruitment partners and personally reaffirm our commitment to investing in, and growing, our office there. We believe that the strong engineering talent we are continuing to find in Sofia will be integral to realising our vision of where ... Read More

Feed: SAS Blogs. Author: Rick Wicklin. I think every course in exploratory data analysis should begin by studying Anscombe's quartet. Anscombe's quartet is a set of four data sets (N=11) that have nearly identical descriptive statistics but different graphical properties. They are a great reminder of why you should graph your data. You can read about Anscombe's quartet on Wikipedia, or check out a quick visual summary by my colleague Robert Allison. Anscombe's first two examples are shown below: The Wikipedia article states, "It is not known how Anscombe created his data sets." Really? Creating different data sets that have ... Read More

Feed: Neo4j Graph Database Platform. Author: Jocelyn Hoppa. By Andy Robbins, Adversary Resilience Lead at SpecterOps | April 17, 2019Reading time: 14 minutes Editor’s Note: This presentation was given by Andy Robbins at GraphConnect New York in October 2017.Presentation SummarySpecterOps provides adversary simulation, adversary detection and adversary resilience to companies looking to assess their current cybersecurity measures. Their experts have worked in defending government agencies as well as worldwide enterprises in the financial services, healthcare, technology, media and communications industries. In this presentation, Resilience Lead, Andy Robbins will dive into how graphs have changed the way hackers attack. He acknowledges ... Read More

Feed: R-bloggers. Author: Michael Toth. When it comes to data visualization, it can be fun to think of all the flashy and exciting ways to display a dataset. But if you’re trying to convey information, flashy isn’t always the way to go. In fact, one of the most powerful ways to communicate the relationship between two variables is the simple line graph. A line graph is a type of graph that displays information as a series of data points connected by straight line segments. The price of Netflix stock (NFLX) displayed as a line graph Line graph of average monthly ... Read More