| 词条 | IBM Data Science Experience |
| 释义 |
In DSX, a data scientist can create a project with a group of collaborators, all having access to various analytics models and using various languages (R/Python/Scala). DSX brings together staple open source tools including RStudio, Spark and Python in an integrated environment, along with additional tools such as a managed Spark service and data shaping facilities, in a secure and governed environment.[2] Data Science Experience provides access to data sets that are available through Watson Data Platform, on-premises or on the cloud. The platform also has a large community and embedded resources such as articles on the latest developments from the data science world and public data sets. DSX is available in on-premises, cloud, and desktop forms. Microsoft and other technology vendors also have products in the machine learning market, which is developing rapidly.[3] HistoryIBM announced the launch of DSX at the Spark Summit 2016 in San Francisco. IBM invested $300 million in efforts to make Spark the analytics operating system for all of the company's big data efforts.[4] In June 2017, Hortonworks and IBM announced their partnership to collaborate on IBM's Data Science Experience. DSX addresses every step of the Data Science lifecycle, offering notebooks, collaboration spaces, tutorials, Machine Learning models and support for Spark, R, Python, and other ML languages.[5] Hortonworks previously had a partnership relationship with Microsoft.[6] See also
References1. ^{{Cite web|url=https://medium.com/@ostechtalks/ibm-data-science-experience-what-is-it-24d2eb3550dc|title=IBM - Data Science Experience, what is it?|last=|first=|date=|website=|language=|archive-url=|archive-date=|dead-url=|access-date=}} 2. ^{{Cite news|url=https://www.computerworld.com/article/3079986/big-data/ibm-targets-data-scientists-with-a-new-development-platform-based-on-apache-spark.html|title=IBM targets data scientists with a new development platform based on Apache Spark|last=Noyes|first=Katherine|work=Computerworld|access-date=2017-09-11|language=en}} 3. ^{{Cite news|url=http://fortune.com/2015/09/14/technology-artificial-intelligence/|title=Apple, Microsoft, and Google vie for control of artificial intelligence market|access-date=2017-09-15|language=en-US}} 4. ^{{Cite news|url=http://www.eweek.com/database/ibm-launches-apache-spark-based-data-science-experience|title=IBM Launches Apache Spark-Based Data Science Experience|work=eWEEK|access-date=2017-09-11|language=en-US}} 5. ^{{Cite news|url=https://hortonworks.com/blog/exciting-data-science-experience-hdp/|title=An Exciting Data Science Experience on HDP - Hortonworks|date=2017-08-09|work=Hortonworks|access-date=2017-09-11|language=en-US}} 6. ^{{Cite news|url=https://go.forrester.com/blogs/17-06-13-hortonworks_eats_ibm_and_loves_it/|title=Hortonworks Eats IBM — And Loves It · Forrester|date=2017-06-13|work=Forrester|access-date=2017-09-15|language=en-US}} 7. ^{{Cite news|url=https://venturebeat.com/2018/05/16/oracle-acquires-machine-learning-platform-datascience-com/|title=Oracle acquires machine learning platform Datascience.com|date=2018-05-16|work=VentureBeat|access-date=2018-05-24|language=en-US}} 1 : IBM software |
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