Gourav Shah initcron

import mlflow
from mlflow.models import infer_signature
from sklearn.linear_model import LinearRegression
from sklearn.datasets import make_regression
from sklearn.metrics import mean_squared_error

# 1. Set tracking URI to local MLflow server
mlflow.set_tracking_uri("http://host.docker.internal:5555")
print("📡 Tracking to:", mlflow.get_tracking_uri())

# Step 0 / Cell 0
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.datasets import load_iris
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report, r2_score, mean_squared_error

	services:
	fastapi:
	image: docker.io/xxxxxx/fastapi:dev.
	build:
	context: "./"
	dockerfile: "Dockerfile"
	ports:
	- "8000:8000"

	streamlit:

	apiVersion: argoproj.io/v1alpha1
	kind: Application
	metadata:
	name: vote-prod
	namespace: argocd
	spec:
	destination:
	namespace: prod
	server: https://kubernetes.default.svc
	project: default

	FROM maven:3.9.6-eclipse-temurin-17 AS build
	WORKDIR /app
	COPY . .
	RUN mvn package -DskipTests


	FROM eclipse-temurin:17-jre-noble as package
	WORKDIR /app
	COPY --from=build /app/target/sysfoo-*.jar ./sysfoo.jar
	EXPOSE 8080

	docker_bnp:
	runs-on: ubuntu-latest
	needs: package
	steps:
	- name: Checkout code
	uses: actions/checkout@v2

	- name: Build and test Docker image
	run: \|
	COMMIT_HASH=$(echo ${{ github.sha }} \| cut -c1-7)

	package:
	runs-on: ubuntu-latest
	needs: test
	steps:
	- uses: actions/checkout@v3

	- name: Set up JDK 17
	uses: actions/setup-java@v3
	with:
	java-version: '17'

	test:
	runs-on: ubuntu-latest
	needs: build
	strategy:
	matrix:
	job: [unit-test, sca, sbom]
	name: Run ${{ matrix.job }}
	steps:
	- name: Checkout code
	uses: actions/checkout@v3

	name: CI Pipeline

	on:
	push:
	branches:
	- main
	pull_request:

	jobs:
	build: