Difference between revisions of "Machine Learning Services"

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!colspan="3" style="width:100%; border-left:solid 2px #ededed; border-right:solid 0px #ededed; border-top:solid 2px #ededed;border-bottom:solid 0px #ededed; background-color:#ededed; font-size:14px; color:#000000; text-align:center" | Machine Learning Services
 
!colspan="3" style="width:100%; border-left:solid 2px #ededed; border-right:solid 0px #ededed; border-top:solid 2px #ededed;border-bottom:solid 0px #ededed; background-color:#ededed; font-size:14px; color:#000000; text-align:center" | Machine Learning Services
 
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|style="width:33%; border-left:solid 2px #ededed;border-right:solid 0px #ededed;border-top:solid 0px #ededed;border-bottom:solid 0px #ededed; text-align:center; background-color:#ffffff"| <br />[[File:TBD.png|thumb|300px|center|Machine Learning Services: what we offer in short]]
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'''Model design'''
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|style="width:33%; border-left:solid 0px #ededed;border-right:solid 0px #ededed;border-top:solid 0px #ededed;border-bottom:solid 0px #ededed; text-align:center; background-color:#ffffff"| <br />[[File:TBD.png|thumb|300px|center|Machine Learning Services: the on board mechanism]]
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* PoC design for dataset acquisition
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|style="width:33%; border-left:solid 0px #ededed;border-right:solid 2px #ededed;border-top:solid 0px #ededed;border-bottom:solid 0px #ededed; text-align:center; background-color:#ffffff"|<br /> [[File:TBD.png|thumb|300px|center|Machine Learning Services: the deployment]]
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* Dataset recording
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* Model design and definition (using the most popular techniques depending on the Scope of Supply)
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* Dataset analysis and preparation for Learning and Training phase
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|style="width:33%; border-left:solid 0px #ededed;border-right:solid 0px #ededed;border-top:solid 0px #ededed;border-bottom:solid 2px #ededed; text-align:left; vertical-align:top; background-color:#ffffff"| <br />[[File:002425_%2B0.003355520.png|none|x150px|center|]]<br />
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'''Model Learning and Training'''
 
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* Model deployment on target
 
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* Design of Learning machine on local or cloud solution
 
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* test bench based solution for accuracy evaluation
 
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* Deployment on the field and fine tuning
 
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|style="width:33%; border-left:solid 0px #ededed;border-right:solid 2px #ededed;border-top:solid 0px #ededed;border-bottom:solid 2px #ededed; text-align:left; vertical-align:top; background-color:#ffffff"|<br /> [[File:ML-TN-001-MPSoC-PL1.png|none|x150px|center|]]<br />
 
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'''Continuous Learning and Update'''
 
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* IoT based continuous recording of new dataset information
 
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* New dataset information review and integration
 
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* Continuous model Training and Learning
 
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* Deployment OTA on the field of new model updates
 
 
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| style="width:25%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: what we offer in short
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| style="width:30%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: what we offer in short
 
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| style="width:25%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: the on board mechanism
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| style="width:30%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: the on board mechanism
 
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| style="width:1%; border-left:solid 0px #ededed;border-right:solid 0px #ededed;border-top:solid 2px #ffffff;border-bottom:solid 0px #ededed; background-color:#ffffff" |
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| style="width:25%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: the deployment
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| style="width:30%; border-left:solid 2px #ededed;border-right:solid 2px #ededed;border-top:solid 2px #ededed;border-bottom:solid 2px #ededed; background-color:#ededed; text-align:left; font-size:14px; color:#000000" |Machine Learning Services: the deployment
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| style="width:1%; border-left:solid 0px #ededed;border-right:solid 0px #ededed;border-top:solid 2px #ffffff;border-bottom:solid 0px #ededed; background-color:#ffffff" |
 
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DAVE Embedded Systems offers the above services with two possible approaches:
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* TBD
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* based on binding formal quotation after discussions and effort evaluation
 
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* based on Time & Material approach with an initial estimation of the effort
 
 
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The standard approach requires an initial contact with the [https://www.dave.eu/get-a-quote technical team]. Customers together the team defines:
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* TBD
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* The technical specification
 
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* The scope of Supply
 
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* The Acceptance Criterias jointly used for evaluate the task and approve it
 
 
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Depending on the requested task, the project is managed via gantt approach with multiple tasks with peer review (both internals and shared with customers). The typical deployment is then shared with customers via a dedicated wiki structure (like this but private between DAVE Embedded Systems and customers) and a dedicated project branch on our Gitlab server.
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* TBD
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Depending on the requested task, the project may require a regular service for updates and improvements (such as the improvement s on ML model thanks to an increased/modified dataset). In this case, this service is released regularly via sw updates in our Gitlab server with release candidates and official releases
 
 
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* [http://mirror.dave.eu/marketing/Services/Machine%20Learning/Datasheets/Datasheet%20ML%20Services%20EN.pdf Brochure PDF ]
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* [link_TBD  {{{nome-som}}} SOM Brochure PDF ]
 
* {{CustomerService}}
 
* {{CustomerService}}
 
* [[Dave_Developer%27s_Wiki_Conventions#RSS_Feeds| RSS feeding]]
 
* [[Dave_Developer%27s_Wiki_Conventions#RSS_Feeds| RSS feeding]]
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* [[:Category:Machine Learning | Category Machine Learning Services]]
 
* [[:Category:Machine Learning | Category Machine Learning Services]]
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* [[:Category:Machine Learning AN| Machine Learning Application Notes]]
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* [[TBD | Machine Learning Application Notes]]
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* [[:Category:Machine Learning TN| Machine Learning Technical Notes]]
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* [[TBD | Machine Learning Technical Notes]]
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* [[:Category:Machine Learning WP| Machine Learning White Papers]]
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* [[TBD | Machine Learning White Papers]]
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* [[:Category:Machine Learning CH| Machine Learning Case Histories]]
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* [[TBD | Machine Learning Case Histories]]
 
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[[Category:Machine Learning]]
 
[[Category:Machine Learning]]

Revision as of 16:43, 30 December 2020

HOME SOMs SBCs ToloMEO Embedded Assistant Sale-tag.pngGET A QUOTE Customer-service.pngONLINE HELPDESK
Roadmap IoT Services ML/AI services Embedded Design Services
Machine Learning Services

Machine Learning Services: what we offer in short
Machine Learning Services: the on board mechanism
Machine Learning Services: the deployment


Machine Learning Services: what we offer in short Machine Learning Services: the on board mechanism Machine Learning Services: the deployment
  • TBD
  • TBD
  • TBD


General Information Pricing Insights
  • [link_TBD {{{nome-som}}} SOM Brochure PDF ]
Customer-service.png Online Technical Helpdesk
Sale-tag.png Machine Learning Services RFQ Request For Quotation
HOME SOMs SBCs ToloMEO Embedded Assistant Sale-tag.pngGET A QUOTE Customer-service.pngONLINE HELPDESK
Roadmap IoT Services ML/AI services Embedded Design Services
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