In recent years, big data has become more popular as businesses of all sizes have discovered how to tap into it when it comes to making crucial decisions. Big data has assisted in finding and fixing problems, tracking business progress, and justifying causes for action. Although there is still much more that we can do […]
Is Your Data At Risk? Here’s How To Protect Your Information Online
If you’ve opened up your inbox only to spot yet another email from a company saying they’ve been affected by a data breach, you know how at-risk your information is in today’s digital world. Cybersecurity is quickly growing as one of the top technology concerns of businesses these days, as private information is being bought […]
Fascinating Ways Big Data and DMPs Are Disrupting Online Publishing
Big data is playing a very important role in content creation. A number of publishers are investing in data-driven strategies to: A few years ago, many experts questioned whether big data was even worth the investment for online publishers. However, more recent studies have shown that is invaluable for boosting revenue. The trick is to […]
Machine Learning meets Social Good to tackle Data Quality Challenges for Enterprises
BigML partners with WorkAround to provide datasets tagged and cleaned by skilled refugees. WorkAround, a crowdsourcing platform for refugees and displaced people, partners with BigML, the leading Machine Learning Platform accessible for everyone, to give more economic opportunities to end users. In a world of increasing automation, it is easy to forget the human work […]
Presentation: Migrating from Big Data Architecture to Spring Cloud
Bio Lenny Jaramillo is Lead Architect, Northern Trust. About the conference Pivotal Training offers a series of hands-on, technical courses prior to SpringOne Platform. Classes are scheduled two full days before the conference and provide you and your team an opportunity to receive in-depth, lab-based training across some of the latest Pivotal technologies.
Principal Component Analysis Webinar Video: Dimensionality Reduction Made Easy!
BigML has brought Principal Component Analysis (PCA) to the platform. PCA is a key unsupervised Machine Learning technique used to transform a given dataset in order to yield uncorrelated features and reduce dimensionality. PCA fundamentally transforms a dataset defined by possibly correlated variables into a set of uncorrelated variables, called principal components. When used for […]
Recapping BigML’s 2018 in Numbers
Another year has gone by in a hurry in the Machine Learning world of BigML. 2018 saw the interest in Machine Learning from all industries continually get stronger. Not only are we seeing an increase in the level of awareness and sophistication towards productive business applications running existing processes more efficiently, but we’re also witnessing novel […]
Principal Component Analysis: Technical Overview
This past week we’ve been blogging about BigML’s new Principal Component Analysis (PCA) feature. In this post, we will continue on that topic and discuss some of the mathematical fundamentals of PCA, and reveal some of the technical details of BigML’s implementation. Let’s revisit our old friend the iris dataset. To simplify visualizations, we’ll just […]
Bringing Automated Machine Learning to the All-in-One Data Warehouse
SlicingDice and BigML partner to bring the very first Data Warehouse embedding Automated Machine Learning. This All-in-One solution will provide guardrails for thousands of organizations struggling to keep up with insight discovery and decision automation goals. Due to the accelerating data growth in our decade, the focus for all businesses has naturally turned to data […]
Automating Principal Component Analysis
Today’s post is the fifth one of our series of blog posts about BigML Principal Component Analysis (PCA) unique implementation, the latest resource added to our platform. PCA is a different type of task in the Data Preparation phase described in the CRISP-DM methodology, which implies the creation of a new dataset based on an existing one. […]