Pipedream ML - No-Code Machine Learning Training

Train machine learning models on AWS SageMaker directly from VSCode. No infrastructure knowledge required.

Features

• 🚀 No-Code Training - Click a button to train ML models
• 🎯 Auto-Configuration - System automatically selects compute resources
• 📊 Real-Time Monitoring - Stream logs and track progress
• 🔧 Framework Support - PyTorch, TensorFlow, scikit-learn, HuggingFace, XGBoost
• 📦 Dataset Management - Upload and manage datasets easily
• 💰 Cost Tracking - Monitor spending in real-time

Quick Start

1. Install Extension

Install from VSCode Marketplace or search for "Pipedream ML"

2. Configure API Key

1. Get your API key from pipedream.in/api-keys
2. Run command: Pipedream: Configure API Key
3. Enter your API key

3. Create or Use Existing Project

New Project:

Command: Pipedream: Create New ML Project
→ Select framework (PyTorch, TensorFlow, etc.)
→ Extension creates template with train.py

Existing Project:

Open your ML project folder in VSCode
→ Extension auto-detects framework
→ Click "Add Pipedream training"
→ Ready to run!

4. Run Training

1. Click "Run Training" button in sidebar
2. Configure dataset and hyperparameters
3. Click "Start Training"
4. Monitor progress in real-time

Supported Frameworks

• PyTorch - Deep learning framework
• TensorFlow - Machine learning platform
• scikit-learn - ML library for Python
• HuggingFace - Transformer models
• XGBoost - Gradient boosting

Commands

• Pipedream: Configure API Key - Set up authentication
• Pipedream: Create New ML Project - Scaffold new project
• Pipedream: Add to Existing Project - Add to existing code
• Pipedream: Run Training - Start training job
• Pipedream: Upload Dataset - Upload training data
• Pipedream: View Training Logs - Stream live logs
• Pipedream: Stop Training - Stop active training
• Pipedream: Download Artifacts - Get trained model
• Pipedream: Check Quota - View plan limits

Requirements

• VSCode 1.85.0 or higher
• Internet connection
• Pipedream account (sign up at pipedream.in)

Extension Settings

• pipedream.apiUrl - Orchestrator API URL
• pipedream.defaultFramework - Default framework for new projects
• pipedream.autoRefreshInterval - Auto-refresh interval (seconds)
• pipedream.notifications.enabled - Enable notifications
• pipedream.notifications.onComplete - Notify on training completion
• pipedream.notifications.onFailure - Notify on training failure

Support

• 📖 Documentation
• 🐛 Report Issues
• 💬 Discord Community
• 📧 Email Support

License

MIT

Enjoy training ML models with zero infrastructure hassle! 🚀