In this contributed article, Lisa Orr, senior data scientist at Urban Airship, describes how her team predicted mobile app user churn and Urban Airship trained and scaled their machine learning model over the last year — and how now it’s reaping valuable insights.
Search Results for: automated model building
Predicting Mobile App User Churn: Training & Scaling Our Machine Learning Model
April 14, 2017 by 1 Comment
DataRobot Adds Deep Learning and New Techniques to Extract Insights from Advanced Models
December 4, 2016 by Leave a Comment
Data science pioneer DataRobot announced the latest version of their enterprise machine learning platform. The new release integrates the powerful TensorFlow™ library for deep learning along with new tools to help users extract insights from all models on the platform. The release also updates DataRobot Prime, a premium add-on that allows users to export scoring code and operationalize models in any environment.
Tomorrow’s Machine Learning Today: Topological Data Analysis, Embedding, and Reinforcement Learning
February 14, 2020 by Leave a Comment
In this contributed article, editorial consultant Jelani Harper highlights how certain visual approaches of graph aware systems will significantly shape the form machine learning takes in the near future, exponentially increasing its value to the enterprise. Developments in topological data analysis, embedding, and reinforcement learning are not only rendering this technology more useful, but much more dependable for a broader array of use cases.
Machine Learning Beyond Predefined Recipes
June 27, 2019 by Leave a Comment
The next evolution in human intelligence is automating the creation of machine learning models to not follow predefined formulas, but rather adapt and evolve according to the problem’s data. While machine learning has enabled massive advancements across industries, it requires significant development and maintenance efforts from data science teams. Enter Darwin, a machine learning tool that automates the building and deployment of models at scale.
SparkCognition’s Darwin Machine Learning Platform Designed to Accelerate Data Science at Scale
May 30, 2019 by 1 Comment
As machine learning technology becomes more widely available on an enterprise scale, differentiating and studying which platform can be best for your business can be difficult. A new white paper from SparkCognition explores one of the solutions on the market that works to accelerate data science at scale. Its Darwin machine learning platform is designed to automate the building and deployment of models.
Darwin Efficacy Report: Accelerating Data Science at Scale by Automation
May 13, 2019 by Leave a Comment
Darwin, a machine learning platform, accelerates data science at scale by automating the building and deployment of models. It provides a productive environment that empowers data scientist with a broad spectrum of experience to quickly prototype use cases and develop, tune, and implement machine learning applications in less time. Download the latest white paper from SparkCognition that compares how Darwin performs against other platforms in the market on the same datasets.
Heard on the Street – 3/28/2024
March 28, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Heard on the Street – 3/7/2024
March 7, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Heard on the Street – 2/29/2024
February 29, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
Heard on the Street – 2/8/2024
February 8, 2024 by Leave a Comment
Welcome to insideBIGDATA’s “Heard on the Street” round-up column! In this regular feature, we highlight thought-leadership commentaries from members of the big data ecosystem. Each edition covers the trends of the day with compelling perspectives that can provide important insights to give you a competitive advantage in the marketplace.
