Tag: datasets

Feed: Featured Blog Posts - Data Science Central. Author: Andrea Manero-Bastin. Quora contribution written by Chomba Bupe. I am actually not even aware of any machine learning (ML) problem that is considered to have been solved recently or in the past. This tells you a lot about how hard things really are in ML. Of course, if you read media outlets, it may seem like researchers are sweeping the floor clean with deep learning (DL), solving ML problems one after the other leaving no stones unturned. In reality, they are not, researchers actually attack relatively simpler problems in the hope ... Read More

Feed: R-bloggers. Author: free range statistics - R. My eye was caught by this tweet by Robin Wigglesworth of the Financial Times with an Alan Smith animation of the US Treasury yield curve from 2005 to 2009. It’s a nice graphic and it made me wonder what it would look like over a longer period.The “yield curve” is the name given to the graphic showing the different annual rates paid on investors who in effect lend money to the US Treasury. In normal circumstances, investors who are prepared to make the loan on a long term basis demand higher effective ... Read More

Feed: Blog – ArangoDB. Author: Christopher Woodward. When looking for a solution for your project, it is important to understand what makes each technology unique, what sets it apart. With ArangoDB that is its native multi-model approach including full graph database capabilities and I am going to explain the fundamental pieces of what that means. Using ArangoDB as a Graph Database If you are already familiar with the graph database concept, then you know that a graph consists of vertices (or nodes) connected via edges. Graph databases usually store edges connected to vertices directly at the vertex object. In ArangoDB ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python, R, Tensorflow, SVM, data reduction, feature selection, experimental design, cross-validation, model fitting, and many more. To keep receiving these articles, sign up on DSC.  34 Great Articles and Tutorials on Clustering How to Automatically Determine the Number of Clusters in your Data  Scale-Invariant Clustering and Regression  Steps to calculate centroids in cluster using K-means clustering algorithm  Classification and Regression Trees  K-nn Clustering Explained in ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Packt Publishing. The diverse fields in which machine learning has proven its worth is nothing short of amazing. At the heart of machine learning are the various algorithms it employs to classify data and predict outcomes. This article highlights two greedy classifiers that, albeit simple, can be extremely powerful in their own right.   This article is an excerpt from the book Machine Learning with R, Third Edition, written by Brett Lantz. This book provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experience ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Paul Pinard. Experiments In his book, The Master Algorithm, Pedro Domingos imagines the following experiments:   Take a building, extremely well–built for two purposes: Nothing can enter and most importantly nothing can leave. The former is to assure the safety of any human from the danger inside, the latter is to assure the safety of everyone on the planet from what is inside. Inside the building, one unlucky fellow finds a 3D printer and the robots it manufactures. The design and algorithms that define and govern each robot are subject to both “mutation” and “mating”. And each created robot has one purpose – to eradicate every other robot. Such a strategy, through selection of the fittest, ... Read More

Feed: R-bloggers. Author: Bob Muenchen. Introduction JASP is a free and open source statistics package that targets beginners looking to point-and-click their way through analyses. This article is one of a series of reviews which aim to help non-programmers choose the Graphical User Interface (GUI) for R, which best meets their needs. Most of these reviews also include cursory descriptions of the programming support that each GUI offers. JASP stands for Jeffreys’ Amazing Statistics Program, a nod to the Bayesian statistician, Sir Harold Jeffreys. It is available for Windows, Mac, Linux, and there is even a cloud version. One of JASP’s key features ... 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: IBM Big Data & Analytics Hub - All Content; Author: paul-bard; The workforce is the core of every business. And while workforce planning can provide great benefit to the growth and profitability of the organization as whole, many HR groups aren’t taking advantage of a sophisticated planning analytics solution.The Aberdeen Group recently published Automate through analytics: Unifying workforce planning through a single system of truth. Aberdeen found that when companies move beyond manual processes, like spreadsheet planning, and unify their workforce data using a central analytics engine—they can significantly improve their “ability to understand emerging workforce pressures, fill new ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Kateryna Lytvynova. Imagine you’re completing a mission in a computer game. Maybe you’re going through a military depot to find a secret weapon. You get points for the right actions (killing an enemy) and lose them for the wrong ones (falling into a pit or getting hit). If you’re playing on high difficulty, you might not conclude this task in just one attempt. Try after try, you learn which consecutive actions are needed to get out of a location safe, armed, and equipped with bonuses like extra health points or small ... Read More