Click to learn more about author Itamar Ben Hamo. Data scientists are some of the most in-demand professionals on the market. A LinkedIn Workforce Report in 2018 found 151,000 unfilled data scientist jobs across the United States, with “acute” shortages in San Francisco, Los Angeles, and New York City. And the demand for data scientists […]
Will They Blend? Theobald Meets HANA
Click to learn more about author Maarit Widmann. In the “Will They Blend?” blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […]
What to Look for in a Model Server to Build Machine Learning-Powered Services
Click to learn more about co- author Ion Stoica. Click to learn more about co- author Ben Lorica. Machine learning is being embedded in applications that involve many data types and data sources. This means that software developers from different backgrounds need to work on projects that involve ML. In our previous post, we listed key […]
Five Key Features for a Machine Learning Platform
Click to learn more about co- author Ion Stoica. Click to learn more about co- author Ben Lorica. Machine learning platform designers need to meet current challenges and plan for future workloads. As machine learning gains a foothold in more and more companies, teams are struggling with the intricacies of managing the machine learning lifecycle. […]
Case Study: Deriving Spark Encoders and Schemas Using Implicits
Click to learn more about author Dávid Szakallas. In recent years, the size and complexity of our Identity Graph, a data lake containing identity information about people and businesses around the world, begged the addition of Big Data technologies in the ingestion process. We used Apache Pig initially, and then migrated to Apache Spark a […]
Deploying the Obscure Python Script: Neuro-Styling of Portrait Pictures
Click to learn more about author Rosaria Silipo. Click to learn more about co-author Mykhailo Lisovyi. Today’s Style: Caravaggio or Picasso? While surfing on the internet a few months ago, we came across this study[i], promising to train a neural network to alter any image according to your preferred painter’s style. These kinds of studies […]
Top Programming Languages for Data Science and Machine Learning
Click to learn more about author Manan Ghadawala. Software developers love arguing about which programming language is the best. However, the criterion for what is “best” is confusing. When we discuss software development for the machine learning and data science fields, this question is timeless and will never lose its relevance. Most useful programming languages […]
Ten Myths About Data Science
Click to learn more about author Daniel Jebaraj. Introduction Data Science is now being used as a competitive weapon. As with other technologies and processes that can transform the way companies operate, there’s a lot of contradictory information about it that’s causing considerable confusion. Most of today’s business leaders have heard that Data Science can […]
Revisiting the Data Science Suitcase
Click to learn more about author Steve Miller. Two years ago, I wrote a blog entitled “What Size is Your Suitcase?” in which I recounted a holiday shopping “dilemma” my wife and I experienced as we purchased mutual gift suitcases. The muddle revolved on which size bags to buy – large ones that could handle […]
Contemporary Data Scientists: Working Machine Learning at Scale
In a recent Magic Quadrant for Data Science and Machine Learning Platforms report, it was expressed that the Data Science and Machine Learning platform market will be in a state of flux over the next few years. Among the drivers of change will be providing Data Scientists with the ability to manage models and collaborate […]