WELCOME
SHAREPOINT SATURDAY OTTAWA
December 3rd, 2016
Vincent Biret
Platinum
Gold
Silver
Bronze
Bronze
6 |SharePoint Saturday AtlantaPlease drink responsibly . We will be happy to call a cab for
you
8 |SharePoint Saturday Atlanta



9 |SharePoint Saturday Atlanta
10 |SharePoint Saturday Atlanta






11 |SharePoint Saturday Atlanta







12 |SharePoint Saturday Atlanta
What is The Graph?
14 |SharePoint Saturday Atlanta
0
1
2
3
4
5
6
Category 1 Category 2 Category 3 Category 4
Title
Series 1 Series 2 Series 3
Sales
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
15 |SharePoint Saturday Atlanta
16 |SharePoint Saturday Atlanta

17 |SharePoint Saturday Atlanta
Vincent
Desk: E43
Phone: 514 444 4444
Extension: 275
Negotium
Street Address: Montreal
Creation : 1/1/00
Technical Advisor
Must do: technical advising
Advantages: better business cards
Developper
Must do: development
Advantages: better keyboard
Works as
Since 1/7/14
Works as
Since 12/7/12
18 |SharePoint Saturday Atlanta



20 |SharePoint Saturday Atlanta




21 |SharePoint Saturday Atlanta
22 |SharePoint Saturday Atlanta








23 |SharePoint Saturday Atlanta
Delve
26 |SharePoint Saturday Atlanta




















MS GraphAPI
31 |SharePoint Saturday Atlanta
32 |SharePoint Saturday Atlanta




33 |SharePoint Saturday Atlanta





34 |SharePoint Saturday Atlanta



35 |SharePoint Saturday Atlanta



36 |SharePoint Saturday Atlanta




37 |SharePoint Saturday Atlanta



38 |SharePoint Saturday Atlanta






With great power comes great responsabilities
40 |SharePoint Saturday Atlanta
41 |SharePoint Saturday Atlanta




42 |SharePoint Saturday Atlanta






ML Studio
Time to day goodbye
45 |SharePoint Saturday Atlanta





46 |SharePoint Saturday Atlanta
Vincent Biret @baywet
Bit.ly/vince365
vbiret@outlook.com

Sps ottawa 2016 vincent biret - Microsoft graph and machine learning

Editor's Notes

  • #9 That among 3D printing, holographic vision, IOT and a few other stuffs
  • #15 Bar chart, pie chart
  • #16 Graph = connected objects by links (generic), graph theory is the study of graph, graph abstract data type implementing graph theory
  • #17 Made for forms data but not really for connected data. That’s why we have to denormalize it which is a huge waste of resources. Other paradigms, Hierachical, NoSQL Document/search, Cubes and Graphs Hierarchical dbs ex : active directory, MMS… or old navigation databases from the 70’s
  • #21 And because it’s trendy Facebook is doing it LinkedIn too (connecting people) Amazon too (IMDB) Google (google knowledge)
  • #22 One endpoint. One auth flow (oauth 2/openid connect)
  • #23 https://graph.microsoft.io/en-us/docs/api-reference/v1.0/resources/opentypeextension https://graph.microsoft.io/en-us/docs/api-reference/v1.0/resources/webhooks https://graph.microsoft.io/en-us/docs/api-reference/beta/resources/identityprotection_root https://graph.microsoft.io/en-us/docs/api-reference/beta/resources/task https://graph.microsoft.io/en-us/docs/api-reference/beta/resources/note
  • #25 Delve is a MS graph client, board, profile explain all that quickly
  • #27 https://msdn.microsoft.com/en-us/office/office365/howto/develop-office-graph
  • #28 https://msdn.microsoft.com/office/office365/HowTo/query-Office-graph-using-gql-with-search-rest-api Use main endpoint with regular data + insights, this is where Microsoft is going to invest. GQL only for advanced graph people, + auth is not brokered…
  • #29 Show the endpoints + resulting json These ones use actors, edges and file types nodes, only 2 endpoints available right now (+/me + /users)
  • #30 https://graph.microsoft.io/en-us/graph-explorer
  • #32 No we don’t have AI robots yet. Yes that’d be awesome. Other last 15 years we’ve made lot of progress in robots, androïd, learning machine, semantic/photo analysis, expert systems… ML is only a small part of what we consider being « artificial thinking » Ex machina
  • #33 Post card systems (80’s), bank fraud detection patterns, insurances, loans….
  • #40 https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-algorithm-cheat-sheet
  • #42 Operated by microsoft https://en.wikipedia.org/wiki/Expert_system
  • #44 Explain workspaces, experiences, training or not, algo, API…