Tag: statistics

Feed: Planet MySQL. Author: Severalnines. The video below details the features and functions that are available in ClusterControl for MySQL Replication.  Included in the video are… How to Deploy Master-Slave Replication How to Deploy Multi-Master Replication MySQL Replication overview including metrics Individual Node overview & management Backup management from Slaves or Masters Adding Nodes Adding Load Balancers ClusterControl Single Console for Your Entire Database Infrastructure Find out what else is new in ClusterControl ClusterControl for MySQL Replication ClusterControl provides advanced deployment, management, monitoring, and scaling functionality to get your MySQL replication instances up-and-running using proven methodologies that you can depend ... Read More

Feed: Microsoft Dynamics 365 Blog. Author: Megan Assarrane. In February 2015, it was discovered that various hackers stole 650 million Eurosfrom over 100 British financial institutions during a two-year span. [1] Six years earlier, in December 2009, Wired already had enough fodder to list the decade’s 10 most dastardly cybercrimes (one dated all the way back to 2000). [2] Despite increases in IT security over the past 16 years, cyber crime is a very real threat to every business with a technological infrastructure. As field service organizations move more and more data online and connect more devices to better anticipate customer needs, ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Leonard Heiler. Data is almost everywhere. The amount of digital data that currently exists is now growing at a rapid pace. The number is doubling every two years and it is completely transforming our basic mode of existence. According to a paper from IBM, about 2.5 billion gigabytes of data had been generated on a daily basis in the year 2012. Another article from Forbes informs us that data is growing at a pace which is faster than ever. The same article suggests that by the year 2020, about 1.7 billion ... Read More

Feed: Planet MySQL. Author: Valeriy Kravchuk. It seems MyRocks is going to become a hot topic in April 2017. Previously (here and there) I tried to compare its performance and scalability vs InnoDB from MySQL 5.7.17 using test case from famous bug #68079. It's an interesting case that took a lot of efforts from Oracle to make InnoDB scale properly, and InnoDB (on my QuadCore box at least, others reported different results on other hardware in comments) still outperformed MyRocks. But maybe it's corner case that is not a big deal in general?Earlier this month I decided to give MyRocks ... Read More

Feed: All Oracle Press Releases. To help management accountants and finance professionals successfully navigate the business and technology changes that are transforming the finance function, Oracle and the American Institute of CPAs (AICPA) today released a new report that details the blueprint for modern finance. The report, Agile Finance Revealed: The New Operating Model for Modern Finance, identifies the traits of agile finance leaders and benchmarks their success in creating a dynamic new operating model that is resilient, responsive, and predictive, helping CFOs and their finance teams to shape the future of the business. “With so much data at their ... Read More

Feed: Microsoft Azure Blog. Author: George Iordanescu. Virtually any data science experiment that uses a new machine learning algorithm requires testing across different scenarios. Simulated data allows one to do this in a controlled and systematic way that is usually not possible with real data. A convenient way to implement and re-use data simulation in Azure Machine Learning (AML) Studio is through a custom R module. Custom R modules combine the convenience of having an R script packaged inside a drag and drop module, with the flexibility of custom code where the user has the freedom of adding and removing ... Read More

Feed: Planet big data. Author: David Smith. When it comes to getting things right in data science, most of the focus goes to the data and the statistical methodology used. But when a misplaced parenthesis can throw off your results entirely, ensuring correctness in your programming is just as important. A new book published by CRC Press, Testing R Code by Richard (Richie) Cotton, provides all the guidance you’ll need to write robust, correct code in the R language. This is not a book exclusively for package developers: data science, after all, is a combination of programming and statistics, and this ... Read More

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. Innovation in data processing and machine learning technology Tuesday, February 21, 2017 By Lorenzo Ridi, Software Engineer & Technical Trainer, Noovle In the right architecture, machine-learning functionality takes data analytics to the next level of value. Editor’s note: This guest post (translated from Italian and originally published in late 2016) by Lorenzo Ridi, of Google Cloud Platform partner Noovle of Italy, describes a POC for building an end-to-end analytic pipeline on GCP that includes machine-learning functionality. “Black Friday” is traditionally the ... Read More

Feed: Planet big data. Author: Meg Blanchette. March 16th, 2017 Editor’s Note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here. We’re just finishing up at Strata + Hadoop World in San Jose this week, where we discussed data platforms and more. Building or rebuilding a data platform can be a daunting task, as most questions that need to be asked have ... Read More

Feed: Planet big data. Author: JeanFrancoisPuget. Feature engineering and feature extraction are key, and time consuming, parts of the machine learning workflow.  They are about transforming training data, augmenting it with additional features, in order to make machine learning algorithms more effective.  Deep learning is changing that according to its promoters.  With deep learning, one can start with raw data as features will be automatically created by the neural network when it learns.  For instance, see this excerpt from Deep Learning and Feature Engineering: The feature engineering approach was the dominant approach till recently when deep learning techniques started demonstrating recognition performance better than ... Read More