Machine Learning Research
Agile Project Methodology
- Client Collaboration
- Business Goals
- Incremental Steps
- Iterative Process
- Adaptive Approach
- Cloud Project Tools
Development Phases
- Requirements
- Use Case
- Data
- Features
- Inference/Prediction
- MLOps
- Standardize
- Automate
- Data Repository
- Software Repository
- ML Artifact Repository
- Model Registry
- Continuous Integration
- Build, Train, Test, Tune
- Deploy, Monitor, Measure, Optimize
- Data Pipeline
- Identify, Acquire, Persist
- Analyze, Filter, Format, Convert, Transform
- Scale, Normalize, Standardize, Validate
- Analytics
- Feature Engineering
- Datasets
- Modeling
- Statistical Analysis
- Regression Analysis
- Forecasting
- Machine Learning
- Supervised
- Unsupervised
- Deep Learning
- Artificial Neural Networks
- Reinforced Learning
- Deployment
- Infrastructure
- Inference Endpoint
- Containerization
- Local
- Cloud
- Framework
- TensorFlow
- PyTorch
- scikit-learn
- Platforms
- AWS
- Azure
- GCP
- Infrastructure
- Integration
- Endpoint Service
- REST API
- Web Service
- Micro Service
- User Interface
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Originally Published 2021-11-04 02:39.00
Updated 2025-03-20 03:43:11 ET