Tag: optimization

Feed: Planet MySQL; Author: Percona Community; Timur Solodovnikov  | July 23, 2019 |  Posted In: MySQL, Open Source Databases Starting at version MySQL5.6+ by default innodb_file_per_table is enabled and all data is stored in separate tablespaces.It provides some advantages. I will highlight some of them:You can reclaim disk space when truncating or dropping a table stored in a file-per-table tablespace. Truncating or dropping tables stored in the shared system tablespace creates free space internally in the system tablespace data files (ibdata files) which can only be used for new InnoDB data.You can store specific tables on separate storage devices, for I/O optimization, space management, ... Read More

Feed: R-bloggers. Author: Thomas Bryce Kelly. So all oceanographers are familiar with the results of gridding, even if they are not so familiar with the process. Gridding is, in general, any method that will take observations and output interpolated (and sometimes extrapolated) data that is placed onto a regular, well-behaving grid. Below is a simple illustration of just such a process where we take scattered observations of temperature and construct a very regular map of temperatures. Gridding can be done to arbitrary resolution (even though the accuracy does not increase!) at the expense of computational resources: Although oceanographers and other ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Andrea Manero-Bastin. This article was written by Louis Tiao.   In this series of notebooks, we demonstrate some useful patterns and recipes for visualizing animating optimization algorithms using Matplotlib.     We shall restrict our attention to 3-dimensional problems for right now (i.e. optimizing over only 2 parameters), though what follows can be extended to higher dimensions by plotting all pairs of parameters against each other, effectively projecting the problem to 3-dimensions. The Wikipedia article on Test functions for optimization has a few functions that are useful for evaluating optimization algorithms. In particular, ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo.  Before I kick off this new blog, I’m happy to announce the release of my 3rd book” "The Art of Thinking Like A Data Scientist”. This book is designed to be a workbook – a pragmatic tool that you can use to help your organization leverage data and analytics to power your business and operational models. The book is jammed with templates, worksheets, examples and hands-on exercises, all composed to help reinforce and deploy the fundamental concepts of Thinking Like A Data Scientist.  I hope you enjoy it! The ... Read More

Feed: AWS Government, Education, & Nonprofits Blog. Author: publicsector. Amazon announced the 11 focus areas of the 2019 Amazon Research Awards, a program that provides up to $80,000 in funding and up to $20,000 in Amazon Web Services (AWS) Promotional Credits to academic researchers investigating topics related to machine learning (ML).This is the fifth year of the program, which in 2018 funded 82 projects. Each grant is intended to support the work of one or two graduate students or postdocs, under the supervision of a tenured faculty member, for one year. Last year’s grant recipients represented 60 universities in 14 ... Read More

Feed: R-bloggers. Author: Kristian Larsen. Category Tags Regression analysis is one of the most demanding machine learning methods in 2019. One group of regression analysis for measuring effects and to evaluate a policy program is Difference-in-Difference. This method is well suited for benchmarking and finding improvements for optimization in organizations. It can, therefore, be used to design organizations so they generate more value for employees and customers. In this article, you learn how to do difference-in-difference in R. Methodology The difference in differences (DiD) method is a statistical technique or quasi-experimental design method, and it is used primarily in the ... Read More

Feed: R-bloggers. Author: R by R(yo). The useR! Conference was held in Toulouse, France and for me thiswas my second useR! after my first in Brisbane last year. This timearound I wanted to write about my experiences and some highlightssimilar to my post on the RStudio::Conference 2019 & Tidyverse DevDayearlier this year. This blog post will be divided into 4 sections: Programming, Shiny, {Packages}, and Touring Toulouse. You can find slides and videos (in a week or so) in: As usual there were many talks that I didn’t get to go to as there arearound 3~5 tracks across different rooms ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Vincent Granville. Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week. To subscribe, follow this link.   Featured Resources and Technical Contributions  Comparing Model Evaluation Techniques - Part 2: Classification and Clustering Data Science using your high school maths knowledge - Gradient Descent Linear and logistic regression in Excel and R - with RegressIt Free book: The Data Engineering cookbook by Andreas Kretz  Try our New Random Number Generator  Visualizing and Animating Optimization Algorithms with Matplotlib  Streamlining Predictive ... Read More

Feed: Planet MySQL; Author: MySQL Performance Blog; See part one of this series here. This post is part two of my series “Assessing MySQL Performance Amongst AWS Options”, taking a look at how current Amazon RDS services – Amazon Aurora and Amazon RDS for MySQL – compare with Percona Server with InnoDB and RocksDB engines on EC2 instances. This time around, I am reviewing the total cost of one test run for each database as well as seeing which databases are the most efficient.First, a quick recap of the evaluation scenario:The benchmark scriptsFor these evaluations, we use the sysbench/tpcc LUA test ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. In “Importance of Thinking Differently…Hint: Don’t Pave the Cow Path”, I introduced the concept of the “3 Horizons of Digital Transformation.”  I wanted to provide a framework that helped organizations differentiate between “Digitalization” versus “Digital Transformation”.  Unfortunately, in succeeding client engagements, I realized I did a crappy job of explaining these 3 horizons.  So, like how bad movies create “Return of” sequels in order to explain everything they screwed up in the original movie, consider this my justification for “Return of the 3 Horizons of Digital Transformation” thriller! This ... Read More