Text mining is becoming an increasingly vital tool for gaining insight from all the text data that flows over the Internet. This overview describes the basic steps of text mining methods and shows how machine learning techniques can help parse natural language processing.
Expand the boundaries of your possibility thanks to Apache Spark. Big data analysis is undergoing a paradigm shift powered by Spark, which supercharges the Hadoop ecosystem to help organizations accomplish things that were once thought impossible.
Rapid advances in cognitive computing and machine learning are enabling smart guidance in many scenarios. Coming on the heels of several key recent announcements, discover how line-of-business and other users can now leverage the full range of analytics—cognitive, descriptive, predictive and
Apache Spark provides a processing framework that is well suited for collaboration among data scientists, developers and data engineers who create highly adaptive solutions. Attendees at Insight 2015 can learn much more about the Spark framework that is built for speed, ease of use and
Text mining is the next step in data mining, offering advanced capabilities for extracting meaning from vast, amorphous masses of data. Despite its complexity, text mining has much to offer businesses—and the list is growing. Discover what text mining could mean for your organization today.
In a world built on sensors, businesses that want to act on data at scale require analytics solutions capable of gaining insights from data in real time, allowing them to make the right decision at the right time.
Game show contestant, medical science researcher and now a legal assistant, IBM Watson continues to expand its cognitive talents into a wide range of professions. Discover why even Watson’s gaffs offer tremendous potential for enhancing tough legal decisions.
So you want to enter the data science field, or maybe you are already a data scientist looking to expand your horizons. Several routes into the profession can provide the core skills, knowledge and best practices necessary to become a developer in the era of cognitive computing. And events such as
At developerWorks Recipes from IBM, novices and experienced developers can access and contribute powerful Internet of Things recipes. This step-by-step tutorial offers a head start on IoT or other applications that connect hardware, run analytics, use machine learning and more.
Find out how Day 3 of the conference offered insight into how data scientists have benefited from the latest approaches to web-scale analytics, including open sourcing of the System ML machine learning library to help the Spark community.
Why are people talking about Apache Spark? It’s because many organizations are using the myriad features of this open source engine to boost their predictive analytics processing. The result? Better, deeper and faster data analyses with reduced coding time and effort.
The current Insight Economy demands a never-ending stream of data-driven discovery. Enter the data scientist—professionals who answer this demand by tapping into big data analytics to uncover emerging trends that help transform organizations.