Fundamentally, machine learning is a productivity tool for data scientists. As the heart of systems that can learn from data, machine learning allows data scientists to train a model on an example data set and then leverage algorithms that automatically generalize and learn both from that example
January marked the release of the long awaited Hidden Figures movie featuring an all-star cast and highlighting the contributions of both women and IBM's technology to history. Hidden Figures tells the true story of three African-American female mathematicians, Katherine Johnson, Mary Jackson, and
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.
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
Elderly care is on tap to be a critical need in the coming decades. See how Caregivers.com is using cloud computing and mobile technologies to provide greater choice for families and higher wages for in-home caregivers.
The unprecedented evolution of social media data’s influence on business can have tremendous impact on how customers are integrated into organizational goals and practices. See why more organizations than ever are using social media data to take a customer-centric approach to evolving their
One thing that a recent event in Beijing, China confirmed is there’s no shortage of interest in machine learning for developers in that region. Take a look at snapshots of event highlights featuring rich content on artificial intelligence, cognitive capabilities, machine learning and more presented
The inability of lines of business to not serve requests because they have to wait for IT provisioning can lead to a proliferation of analytics silos that can cause a loss of control of data. See how the next big stage of analytics with integrated Apache Spark helps organizations understand the
Nancy Hensley, director of offering management for IBM Analytics speaks with Rob Thomas, vice president of development for analytics, at IBM, on the subject of business transformation, leading to a discussion of the data maturity curve.
The Internet of Things (IoT) is making inroads in all areas of life, expanding the opportunities for each new generation of global citizens. What’s more, cloud technology is bringing IoT capabilities to people around the world, bringing them together in a new world of data.
Database migration is not any database administrator’s idea of fun—not even close. By far, the database migration status quo can be the least interesting and most dreaded part of the job. Check out an advanced self-service, ground-to-cloud database migration offering for handling database migration
The concluding week of September 2016 offered much excitement in New York City, the backdrop for Strata + Hadoop World 2016 and several key IBM announcements, including the launch of a cloud-based, self-service environment for data science teams. Enjoy some key highlights captured from this
IBM hosted an exciting event for data and analytics leaders and practitioners this week in New York. At the IBM DataFirst Launch Event, we unveiled new solutions, tools, and approaches for organizations to transform themselves through cognitive computing.