# Install Python 3.9+
sudo apt update
sudo apt install python3.9 python3.9-venv python3-pip

# Install Conda (alternative)
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

# Create virtual environment
python3.9 -m venv ml-env
source ml-env/bin/activate

# Core ML libraries
pip install numpy pandas scikit-learn matplotlib seaborn
pip install tensorflow pytorch torchvision
pip install xgboost lightgbm

# MLOps tools
pip install mlflow dvc wandb
pip install prefect airflow
pip install pytest black flake8

# Serving frameworks
pip install fastapi uvicorn gunicorn
pip install streamlit gradio

# Install Docker
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh

# Add user to docker group
sudo usermod -aG docker $USER

# Install Docker Compose
sudo curl -L "https://github.com/docker/compose/releases/download/v2.20.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

# Install kubectl
curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

# Install minikube for local development
curl -LO https://storage.googleapis.com/minikube/releases/latest/minikube-linux-amd64
sudo install minikube-linux-amd64 /usr/local/bin/minikube

# Install Helm
curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash

{
  "recommendations": [
    "ms-python.python",
    "ms-toolsai.jupyter",
    "ms-azuretools.vscode-docker",
    "ms-kubernetes-tools.vscode-kubernetes-tools",
    "GitHub.copilot",
    "ms-vscode-remote.remote-containers"
  ]
}

# Install AWS CLI
curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install

# Configure credentials
aws configure

# Install gcloud SDK
echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | sudo tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key --keyring /usr/share/keyrings/cloud.google.gpg add -
sudo apt update && sudo apt install google-cloud-cli

# Install Azure CLI
curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
az login

# Check GPU
lspci | grep -i nvidia

# Install CUDA Toolkit
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt update
sudo apt install cuda

# Install cuDNN
# Download from NVIDIA website and install

# Verify installation
nvidia-smi
nvcc --version

# Install PyTorch with CUDA support
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

#!/usr/bin/env python3
"""Verify ML development environment setup."""

import subprocess
import sys

def check_command(cmd, name):
    try:
        result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
        if result.returncode == 0:
            print(f"✓ {name} is installed")
            return True
    except:
        pass
    print(f"✗ {name} is not installed")
    return False

def main():
    checks = [
        ("python3 --version", "Python 3"),
        ("docker --version", "Docker"),
        ("kubectl version --client", "kubectl"),
        ("git --version", "Git"),
        ("aws --version", "AWS CLI"),
    ]
    
    print("Checking environment setup...\n")
    all_good = all(check_command(cmd, name) for cmd, name in checks)
    
    print("\n" + "="*40)
    if all_good:
        print("✓ All checks passed! Environment is ready.")
    else:
        print("✗ Some components are missing. Please install them.")
        sys.exit(1)

if __name__ == "__main__":
    main()