Spark’s built-in machine-learning library (MLlib) provides a key differentiator from predecessor open source technologies and leverages Spark’s distributed, in-memory execution model. Take a look at some practical applications for specific Spark machine-learning algorithms in three advanced
Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building
Download an ebook that gives detailed information for building an app that can not only predict flight delays caused by weather conditions, but also provide the degree to which flights will be delayed.
Machine learning is finding its way into a variety of applications. Discover an open source machine learning platform that combines the data processing power of Spark with powerful machine learning algorithms courtesy of the H2O platform to tackle challenges technologists face when applying machine
Flight delays because of weather are inevitable for frequent flyers and infrequent travelers alike. Fortunately, we are living in an era in which applications such as the flight predictor app can be quickly and cost-effectively designed, built and tested to stay abreast of useful information for
Use open-source tools to supercharge the data science lifecycle, giving data science teams a boost as they work to provide compelling results in the complex team environments that mark modern corporations. Learn how you can make open data science an ongoing part of your business environment when
Whether organizations want to extract customer data beyond names and addresses from unstructured data sources; pull specific dates, times or monetary amounts; predict trends from sentiment data; or engage in many other uses, text analytics is the way to go. Learn the details of text analytics, and
Data science takes collaborate teams of data scientists engaging in productive, open data development initiatives that can ensure strong workflow, governance, security and management. See why open environments are revolutionizing the data science landscape.
A growing number of businesses and industries are finding innovative ways to apply graph analytics to a variety of use-case scenarios because it affords a unique perspective on the analysis of networked entities and their relationships. Gain an understanding of how four different types of graph
Open source is a disruptor that never quits, and it is seemingly penetrating and transforming every aspect of established data, analytics and application ecosystems. Give this podcast, recorded at IBM InterConnect 2016, a listen to learn how open source initiatives are transforming machine learning.
Does your data science need a shot in the arm? Attend Datapalooza, a one-of-a-kind globetrotting data science festival that aims to bring together data scientists from all walks of life for two and a half days of education and application. Find out when Datapalooza will be coming to your area, then
Open source is a disruptor that never quits. It seems to be penetrating and transforming every aspect of established data, analytics and application ecosystems. In this podcast, recorded at IBM InterConnect 2016, listen to David Taieb, a cloud data services developer advocate at IBM, share his
Spark just seems to be getting big play everywhere in the technology arena. What is Spark? And do you need it? Get a good glimpse into its in-memory execution capabilities, some of its key components, its integrations and its availability as a service.
Evolving Internet of Things technology is paving the way for ongoing innovation—from smart thermostats and smart cars to other smart devices—through continuous access to its data streams. And while ongoing access to that data inspires the magic behind Internet of Things solutions, it also offers an
The open source Hadoop framework accommodates distributed storage and processing of large data sets on clusters of computers through the use of programming models. If that description sounds complex, then dig into this breakdown of Hadoop components to gain an understanding of just how flexible