The Weather Company, an IBM Business (NYSE: IBM), introduced a new outage prediction solution designed to help utility companies proactively prepare for and respond to weather-related outages. Tailored to each utility’s storm response plan, The Weather Company’s Outage Prediction solution helps predict the anticipated number of outages and appropriate mobilization level based on the weather forecast for the utility’s service territory.
New Outage Prediction Model From The Weather Company, an IBM Business, Helps Utilities Prepare For and Respond to Severe Weather
In this special guest feature, Christophe Marcant, Senior VP for Strategy & Communication for Stibo Systems, explains how there is great opportunity to leverage machine learning (ML) to adapt data from a source to a consumer faster. So, rather than focusing on enforcing format and meaning to facilitate exchanges, ML will enable organizations to discover patterns in data, propose associations, correlations, and adaptation.
In this contributed article, tech writer Linda Gimmeson goes over a short list of the most popular developer tools for machine learning practitioners including Amazon Machine Learning, Tensor Flow, Azure Machine Learning Studio, H20, Caffe, MLlib, and Torch.
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.
BodiData, Inc. a Silicon Valley-based technology company that specializes in generating big data on three-dimensional body measurements and Alvanon, the global apparel business expert, have signed a strategic partnership agreement that will deliver both big data and analysis on the shape and size of the diverse and complex US consumer population.
In this contributed article, Dan Adika, CEO and cofounder of WalkMe, discusses how big data, combined with machine learning and artificial intelligence, can contextually guide employees on how to use any system, provide businesses with insights into common technology obstacles, and ultimately personalize the user experience to drive greater adoption.
Our friends over at The Data Incubator just released a new series of data-driven ranking reports that showcase the quantitative methodologies the data science fellowship, hiring and training company uses to actively teach their fellows. The idea was to develop a more data-driven approach to what the company should be teaching in their data science corporate training and their free fellowship for masters and PhDs looking to enter data science careers in industry.
Argyle Data has expanded its core machine learning and AI application suite to engage with clients in enterprise areas including IoT security, financial services and online/mobile banking.
At The Data Incubator we pride ourselves on having the latest data science curriculum. Much of our course material is based on feedback from corporate and government partners about the technologies they are looking to learn. This report is the second in a series analyzing data science related topics. We thought it would be useful to the data science community to rank and analyze a variety of topics related to the profession in a simple, easy to digest cheat sheet, ranking, or report. It’s our way of practicing what we teach.
At The Data Incubator we pride ourselves on having the latest data science curriculum. Much of our curriculum is based on feedback from corporate and government partners about the technologies they are looking to learn. However, we wanted to develop a more data-driven approach to what we should be teaching in our data science corporate […]