- Filed under: enosix , enosix integration , enosiX Salesforce integration , enosix SAP integration , Louis Columbus’ blog , Machine learning , McKinsey 2016 Study Tagged: Analytics , enosix , enosix integration , enosiX Salesforce integration , enosix SAP integration , Machine learning , McKinsey Analytics , McKinsey Global Institute’ , McKinsey’s 2016 Analytics Study
- McKinsey identified 120 potential use cases of machine learning in 12 industries and surveyed more than 600 industry experts on their potential impact.
- The study underscores how critical integration is for gaining greater value from data and analytics.
- Design-to-value, supply chain management and after-sales support are three areas where analytics are making a financial contribution in manufacturing.
- Location-based services and U.S. retail are showing the greatest progress capturing value from data and analytics .
These and many other insights are from the McKinsey Global Institute’s study The Age of Analytics: Competing In A Data-Driven World published in collaboration with McKinsey Analytics this month. You can get a copy of the Executive Summary here (28 pp., free, no opt-in, PDF) and the full report (136 pp., free, no opt-in, PDF) here. Five years ago the McKinsey Global Institute (MGI) released Big Data: The Next Frontier For Innovation, Competition, and Productivity (156 pp., free no opt-in, PDF), and in the years since McKinsey sees data science adoption and value accelerate, specifically in the areas of machine learning and deep learning. The study underscores how critical integration is for gaining greater value from data and analytics.
Continue reading “McKinsey’s 2016 Analytics Study Defines The Future Of Machine Learning”
- Our StackGAN for the first time generates 256 x 256 images with photo-realistic details.”
- This piece of work is completely different: after learning the neural networks are able to create something completely new – such as synthesizing new, photorealistic images from a piece of text we have written.
- Home > Cool Tech > Neural network can create high-res images based on
- It’s also fascinating because the two-stage method of drawing images looks, to our way of thinking, a whole lot like the way artists will sketch out a piece of work, and then do a second pass to add detail.
- Neural network can create high-res images based on a text description
In a new piece of research, neural networks have been used to generate high-resolution photos based only on a basic text description.
Continue reading “AI System Can Generate High-Res Images Based On a Text Description”
- The $40 ‘Watch Dogs 2’ Season Pass includes new stories, clothes
- Microsoft CEO says mixed reality is the ‘ultimate computer’
- Ukraine’s military wants HoloLens helmets for its tank commanders
- Nadella admitted that for a long time, Microsoft was complacent. “
- Tap your cheek to ask Siri a question with Bragi Dash update
Microsoft is set to unveil several new products at its fall event on Wednesday, but that hasn’t stopped CEO Satya Nadella from dropping by Laguna Beach, Califor…
Continue reading “Microsoft CEO says mixed reality is the ‘ultimate computer’”
- Simplify Machine Learning with Apache Spark
- Apache Spark and the Apache Spark Logo are trademarks of the Apache Software Foundation.
- Join the Databricks Community Edition beta to get free access to Spark and try out the notebooks.
- A few months ago, we held a live webinar – Apache Spark MLlib: From Quick Start to Scikit-Learn – to give a quick primer on machine learning, Spark MLlib, and an overview of some Spark machine learning use cases.
- Last week, we held a live webinar – GraphFrames: DataFrame-based graphs for Apache Spark – to give an overview, a live demo, and a discussion…
Read the full article, click here.
@kdnuggets: “.@databricks webinar – Spark MLlib: Quick Start to Scikit-Learn #MachineLearning #BigData”
A few months ago, we held a live webinar – Apache Spark MLlib: From Quick Start to Scikit-Learn – to give a quick primer on machine learning, Spark MLlib, and an overview of some Spark machine learning use cases. It also covered multiple Spark MLlib quick start demos as well as the integration of common data science tools like Python pandas, scikit-learn, and R with MLlib.
Apache Spark MLlib: From Quick Start to Scikit-Learn