http://dbpedia.org/ontology/abstract
|
The IBM Machine Learning Hub hosts busines … The IBM Machine Learning Hub hosts businesses wanting to collaborate with IBM’s machine learning experts. Its mission is to close the gap between available open-source tools and the knowledge required to use them. During three-day workshops, the machine learning experts work with companies to implement initial prototypes. Within the workshops, data scientists use tools like Data Science Experience (DSX) to collaborate and find similar solutions to their use cases. The machine learning experts have completed cases in the travel, energy and utilities, healthcare, financial services, manufacturing, and retail industries. Together, they walk through the stages of the machine learning process to get the concrete results. The Machine Learning Hub's data scientists and machine learning engineers actively contribute to open source projects while also writing academic papers – continually investigating new avenues of inquiry and sharing their knowledge with the community. There are currently six IBM Machine Learning Hubs around the world: San Jose, Toronto, Ottawa, Stuttgart, Bangalore, and Beijing.Ottawa, Stuttgart, Bangalore, and Beijing.
|
http://dbpedia.org/ontology/wikiPageID
|
55208025
|
http://dbpedia.org/ontology/wikiPageLength
|
2639
|
http://dbpedia.org/ontology/wikiPageRevisionID
|
1072386867
|
http://dbpedia.org/ontology/wikiPageWikiLink
|
http://dbpedia.org/resource/Toronto +
, http://dbpedia.org/resource/Information_technology +
, http://dbpedia.org/resource/Cognitive_computing +
, http://dbpedia.org/resource/Financial_services +
, http://dbpedia.org/resource/Ottawa +
, http://dbpedia.org/resource/Stuttgart +
, http://dbpedia.org/resource/Bangalore +
, http://dbpedia.org/resource/Open-source_software +
, http://dbpedia.org/resource/Beijing +
, http://dbpedia.org/resource/IBM_Data_Science_Experience +
, http://dbpedia.org/resource/Travel +
, http://dbpedia.org/resource/Silicon_Valley +
, http://dbpedia.org/resource/Health_care +
, http://dbpedia.org/resource/Open-source_model +
, http://dbpedia.org/resource/San_Jose%2C_California +
, http://dbpedia.org/resource/IBM +
, http://dbpedia.org/resource/Retail +
, http://dbpedia.org/resource/Category:IBM +
, http://dbpedia.org/resource/Data_science +
, http://dbpedia.org/resource/Machine_learning +
, http://dbpedia.org/resource/Manufacturing +
|
http://dbpedia.org/property/wikiPageUsesTemplate
|
http://dbpedia.org/resource/Template:Reflist +
, http://dbpedia.org/resource/Template:Advert +
, http://dbpedia.org/resource/Template:Multiple_issues +
, http://dbpedia.org/resource/Template:COI +
|
http://purl.org/dc/terms/subject
|
http://dbpedia.org/resource/Category:IBM +
|
http://www.w3.org/ns/prov#wasDerivedFrom
|
http://en.wikipedia.org/wiki/IBM_Machine_Learning_Hub?oldid=1072386867&ns=0 +
|
http://xmlns.com/foaf/0.1/isPrimaryTopicOf
|
http://en.wikipedia.org/wiki/IBM_Machine_Learning_Hub +
|
owl:sameAs |
http://dbpedia.org/resource/IBM_Machine_Learning_Hub +
, https://global.dbpedia.org/id/3z9mY +
, http://www.wikidata.org/entity/Q43080497 +
|
rdfs:comment |
The IBM Machine Learning Hub hosts busines … The IBM Machine Learning Hub hosts businesses wanting to collaborate with IBM’s machine learning experts. Its mission is to close the gap between available open-source tools and the knowledge required to use them. During three-day workshops, the machine learning experts work with companies to implement initial prototypes. Within the workshops, data scientists use tools like Data Science Experience (DSX) to collaborate and find similar solutions to their use cases. The machine learning experts have completed cases in the travel, energy and utilities, healthcare, financial services, manufacturing, and retail industries. Together, they walk through the stages of the machine learning process to get the concrete results.rning process to get the concrete results.
|
rdfs:label |
IBM Machine Learning Hub
|