J White Bear is a data scientist and software engineer at IBM. In this podcast, White Bear discusses simultaneous localization and mapping, an ongoing research area in robotics for autonomous vehicles and well-recognized as a nontrivial problem space in both industry and research.
IBM’s community of big data developers continues to grow. As our Big Data Developer meetup program moves into its fifth year, this worldwide community of customers, partners and IBM developers is on the verge of enlisting its 100,000th member—when we published this blog, we counted 99,100.
Seth Dobrin is vice president and CDO, IBM Analytics, platform development, at IBM. In this podcast, Dobrin shares experiences using Apache Spark for data science transformation and some thoughts on a larger vision for data science transformation at scale.
Steven Astorino is Vice President, Development, IBM Private Cloud Analytics Platform. In this podcast, he discusses how machine learning is driving the evolution of data science in strategic business initiatives.
It is said that more data has been created in the past two years than in the entire preceding history of mankind. It would be interesting to find out how much of this data has been analyzed and put to good use. Analyzing and harnessing big data is undoubtedly the major challenge of the day for all
IoT is the next goldmine of data. Today, it’s still largely untapped information that is primarily used for operational monitoring. By combining that data with traditional “corporate” data, you can improve customer service through faster problem recognition and response, react more quickly to a
In this white paper, discover how programmers and data scientists can use SparkR to transform R into a tool for big data analytics, taking advantage of parallel processing and near-linear scaling to tackle much larger challenges than would normally be possible with other methods.
Analyzing streams of big data in real time can have a big impact on competitive advantage. In a world of bewildering stream processing engine choices, explore the use-case-dependent alternatives that can provide well-suited business outcomes, courtesy of expertise from Roger Rea and Jacques Roy.
Internet of Things data, devices and technologies are evolving into a core platform that is expected to impact business flexibility and more. Take a look at some key comprehensive best practices for Internet of Things–enabled application development that can put speed and agility into your business
Holden Karau is a software engineer at IBM, an active open source contributor and coauthor of Learning Spark (O'Reilly Media, February 2015) and the soon to be released High Performance Spark (O'Reilly Media, March 2017). In this podcast, Karau examines how to effectively search logs from Apache
Nick Pentreath is a principal engineer at IBM, a member of the Apache Spark project management committee (PMC) and author of Machine Learning with Spark (Packt Publishing, December 2014). In this podcast, Pentreath covers the basics of feature hashing and how to use it for all feature types in
Today’s businesses need a culture of collaboration that empowers knowledge workers to glean cognitive insights from data that help transform and modernize operations. See how cloud-based platforms and solutions enable data scientists and other experts to exploit artificial intelligence, machine
The GDPR enhances the data protection rights of EU data subjects’ data worldwide. It codifies and clarifies data subjects’ ability to request access to and erasure of their information (right to erase/to be forgotten). In addition, organizations need to provide easier access to personal data, with
Emily Curtin is a software engineer at The Weather Company (now IBM) working on the data engineering platform team. Robbie Strickland is vice president, engines and pipelines, IBM Watson Data Platform, at IBM. In this podcast, they give a technical overview of how Parquet works and how recent