In the past couple of years, we here at the insideBIGDATA brain trust have noticed a significant upward trend for all that is machine learning – technology, vendors, applications, tools, use cases, educational resources, and much more. Machine learning can be thought of as a set of tools and methods that attempt to infer patterns and extract insight from observations made of the physical world. The subject of machine learning is one that has matured considerably over the past sever years and has grown to be the facilitator of both data science and big data. Much of machine learning’s current embodiment depends on new capabilities of hardware utilizing cloud storage solutions and high-performing parallel architectures such as Apache Hadoop and Spark.
As a result machine learning’s rise, we’re excited to announce a new direction here at insideBIGDATA. Moving forward, we’re adding the “Your Source for Machine Learning” to our tagline. This means that your favorite news destination will have a machine learning “flavor” in terms of our editorial content.
This pivot delights me no end. As a practicing data scientist myself, most of the projects I work on involve various elements of machine learning. In fact, I recently wrote my “Machine Learning Manifesto” that outlines why this technology is important to the global business community. It is for many of the reasons outlined in the manifesto that we’re making this change. By many measures, this is an area of continued hyper-growth as more intelligence is required of modern business applications.
Our goal is to bring our valued readers from around the world, late breaking news surrounding this field. Since big data and data science are both driven by machine learning methods, we’ll continue to bring you a well-balanced slice of these areas as well. Our focus, quite simply, will be honed a bit more. We hope you like the new emphasis and we’d love to hear from you about it. You can contact me directly at: firstname.lastname@example.org.
Contributed by: Daniel D. Gutierrez, Managing Editor of insideBIGDATA. He is also a practicing data scientist through his consultancy AMULET Analytics. Daniel just had his most recent book published, Machine Learning and Data Science: An Introduction to Statistical Learning Methods with R.