Businesses have come to expect that smart rivals wielding digital technologies will disrupt their competitive landscapes. How ready is your organization to be a digital disruptor? Take a look at detailed criteria for assessing your organization’s readiness and the strategic steps you can take to
In this episode of the Finance in Focus podcast, listen as wealth management experts Marc Andrews and April Rudin discuss ways that financial institutions can use cognitive computing to find solid ground in shifting regulatory terrain.
The Internet of Things continues to be a land of opportunity in so many areas. Take a look at this overview of steps to innovation and success factors along with the risks and pitfalls to avoid in your Internet of Things journey.
Nick Pentreath of the Spark Technology Center teamed up with Jean-François Puget of IBM Analytics to deliver the main talk of the Spark & Machine Learning Meetup in Brussels, "Creating an end-to-end Recommender System with Apache Spark and Elasticsearch."
At the recent Spark & Machine Learning Meetup in Brussels, Holden Karau of the Spark Technology Center delivered a lightning talk called "A very brief introduction to extending Spark ML for custom models."
At the Spark & Machine Learning Meetup in Brussels on October 27, 2016, Pierre Borckmans of Real Impact Analytics delivered a lightning talk called "Writing Spark applications, the easy way: How to focus on your data pipelines and forget about the rest."
Countering fraud is an ongoing process in the world of finance, but it need not be an overwhelming one. When identifying fraudulent activity amid the millions of transactions that flood financial networks, IBM Safer Payments offers ways to help manage workloads while avoiding false positives.
Discover some of the latest and greatest developments in the world of Apache Spark in this retrospective on Spark Summit Europe 2016. When you do, find out how modern developers are connecting their data sources to Spark in exciting ways, and learn how the cloud is providing access to Spark-powered
The combination of Jupyter Notebooks, Apache Hadoop and Apache Spark has become a killer app for data practitioners. It unlocks the ability to explore, visualize and experiment with both structured and unstructured data sets with great ease and efficiency. We spoke recently with Chris Snow at IBM
Automation can be a great solution for highly manual processes, but its implementation has its detractors. Can robotic process automation be successful in providing an artificial intelligence solution that includes machine learning for further streamlining typically manually intensive processes?
Apache Spark, sometimes called the “analytics operating system,” is empowering organizations of all kinds through machine learning by helping them create unprecedented value from their data. Discover eight ways that Apache Spark’s machine learning capabilities are driving the modern business.