dotnet tool install --global dotnet-ef --version 3.1.1
Install-Package Microsoft.EntityFrameworkCore.Design into FootballPredictor.Api
dotnet ef migrations add InitialCreate -s .\src\hosts\FootballPredictor.Api\ -p .\src\libraries\Data\FootballPredictor.Data.EFCore.PostgreSQL\
dotnet ef migrations remove -s .\src\hosts\FootballPredictor.Api\ -p .\src\libraries\Data\FootballPredictor.Data.EFCore.PostgreSQL\
dotnet ef database update -s .\src\hosts\FootballPredictor.Api\ -p .\src\libraries\Data\FootballPredictor.Data.EFCore.PostgreSQL\
GET /v2/competitions/PL/matches?matchday=26&season=2019 HTTP/1.1
Host: api.football-data.org
X-Auth-Token: >>> TOKEN GOES HERE <<<
POST /match HTTP/1.1
Host: localhost:5000
Content-Type: application/json
{
"Competition" : "PL",
"Matchday" : 1,
"Season" : 2018
}
GET /match/predict HTTP/1.1
Host: localhost:5000
Content-Type: application/json
{
"HomeTeam" : "Tottenham Hotspur FC",
"AwayTeam" : "Manchester City FC"
}
GET /match/fixtures HTTP/1.1
Host: localhost:5000
Content-Type: application/json
{
"Competition" : "PL",
"Matchday" : 26,
"Season" : 2019
}
POST /match/update-model HTTP/1.1
Host: localhost:5000
Content-Type: application/json
SELECT
CAST("public"."Matches"."Id" as REAL) as "Id",
CAST("public"."Matches"."MatchId" as REAL) as "MatchId",
CAST("public"."Matches"."SeasonId" as REAL) as "SeasonId",
"public"."Matches"."Matchday",
"public"."Matches"."HomeTeam",
CAST("public"."Matches"."HomeTeamId" as REAL) as "HomeTeamId",
"public"."Matches"."AwayTeam",
CAST("public"."Matches"."AwayTeamId" as REAL) as "AwayTeamId",
"public"."Matches"."Winner",
CAST("public"."Matches"."WinnerId" as REAL) as "WinnerId",
CAST("public"."Matches"."HomeTeamGoals" as REAL) as "HomeTeamGoals",
CAST("public"."Matches"."AwayTeamGoals" as REAL) as "AwayTeamGoals"
FROM "public"."Matches"
docker run -e ACCEPT_EULA=Y -v /path/to/seq/data:/data -p 80:80 -p 5341:5341 datalust/seq:latest
https://towardsdatascience.com/introduction-to-machine-learning-in-c-with-ml-net-bf45502d8110