🗃️ Data & Preprocessing

Data Sources:

• Kaggle Datasets
• UCI ML Repository
• Google Dataset Search
• AWS Open Data

Processing Tools:

Data Quality:

• Great Expectations
• Evidently AI
• Deepchecks

🔧 ML Frameworks

Deep Learning:

Traditional ML:

Specialized:

• Hugging Face (NLP/Vision)
• SpaCy (NLP)
• OpenCV (Computer Vision)
• NetworkX (Graph ML)

☁️ Cloud & Compute

Major Providers:

Specialized Platforms:

• Databricks
• Snowflake
• Paperspace
• Colab/Kaggle

Hardware:

• NVIDIA GPUs (A100, H100)
• Google TPUs
• AWS Inferentia
• Apple Silicon

🧠 Model Development

Experiment Tracking:

AutoML:

• AutoKeras
• H2O.ai
• Google AutoML
• Auto-sklearn

Model Architecture:

• Transformer Models
• Convolutional Networks
• Recurrent Networks
• Graph Neural Networks

🚀 MLOps & Deployment

Orchestration:

Model Serving:

• TensorFlow Serving
• TorchServe
• MLflow Models
• Seldon Core

Containerization:

• Docker
• Kubernetes
• Helm Charts
• Istio Service Mesh

📊 Monitoring & Observability

Model Monitoring:

• Evidently AI
• Arize AI
• Fiddler
• WhyLabs

Performance Metrics:

• Data Drift Detection
• Model Bias Analysis
• Latency Monitoring
• A/B Testing

Visualization: