Home Data News 25th Jan 2018 – Data Science News Daily Roundup

25th Jan 2018 – Data Science News Daily Roundup

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Microsoft’s New Windows Desktop Program, SAP HANA adds Geospatial Data, Alphabet launches Chronicle, and more in today’s top stories around machine learning, deep learning,and data science news.

1. Microsoft’s New Windows Desktop Program Analytics for developers

Microsoft has launched a new online toolkit that developers can use to analyze how well their software is performing. It can identify bugs and other potential issues that detract from the user experience. The new Windows Desktop Program is a one-stop portal to view their desktop application analytics or access the data via an API.

On signing up for the Windows Desktop Application Program and registering your certificates, one will be able to use the analytics reports to:

  • View a summary of all failure types, sorted by number of hits
  • Drill down into each failure and download stack traces and CAB files to debug the issue faster
  • Compare the health status and adoption of a newly released version of your application to previous releases
  • View health data in aggregate or by region, allowing you to isolate issues that are specific to a region
  • Compare performance and adoption of your desktop applications across Windows versions, such as the latest Windows 10 or Windows Insider releases.
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To know more about the Windows Desktop Application Program, check out the video from the Windows Developer series.

2. SAP HANA adds Geospatial Data to its database offerings

SAP announced that it is adding geospatial data to its growing list of database offerings as it launches a partnership with spatial analytics specialist Esri. The aim of this partnership is to adopt SAP’s in-memory data and application development platform.

Esri would run its ArcGIS enterprise geodatabase on the SAP HANA platform. The integration is designed to boost performance and scaling with the goal of integrating location with other enterprise data sets. Among the promised applications are geographic information systems (GIS), mapping, advanced visualizations and spatial analytics.

For a detailed information on this topic, visit the website.

3. Alphabet launches Chronicle to track hackers with the help of machine learning

Alphabet, the parent company of Google launched Chronicle.

Chronicle is developing technology that finds hackers faster than humans currently can. The company would build tools that use machine learning to identify the signs of hackers in company systems and shorten the amount of time it takes to stop a breach. It also joins a crowded field of cybersecurity firms that are trying to help companies find hackers sooner.

Chronicle aims to give organizations a much higher-resolution view of their security situation. This is done by combining machine learning, large amounts of computing power and large amounts of storage.

Click to know more about Chronicle on this website.

4. BigTime Software launches reporting and data analytics tool

BigTime Software, Inc.,announced the launch of its resource allocation product within its Premier platform. The new product or more precisely the tool gives enterprise managers a real-time view of reporting and data analytics. The product is SaaS-based and is scalable to hundreds of enterprise users.

Brian Saunders, CEO of BigTime Software, stated,“We accelerated the rollout of our Premier product based on the demand from beta customers who said the platform had an immediate impact on project visibility and profitability, particularly in managing multiple projects and large staffing teams across multiple time zones.”

Click on the link for a detailed information on this topic.

5. Ray framework close to production-ready

Ray, a high-performance distributed execution framework is targeted at large-scale machine learning and reinforcement learning applications. It is being developed by a team of UC Berkeley professors including Ion Stoica, who has previously developed large scale systems like Apache Spark.

Ray comes with two libraries for accelerating deep learning and reinforcement learning development:

  • Ray Tune: Hyperparameter Optimization Framework
  • Ray RLlib: Scalable Reinforcement Learning Library

To explore Ray framework visit the codebase on GitHub and its documentation.

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