Machine Learning (ML) Development
Machine Learning (ML) Development
- Data preprocessing and feature engineering
- Supervised, unsupervised, and reinforcement learning algorithms
- Model selection, hyperparameter tuning, and cross-validation
- Deployment pipelines with containerization (Docker, Kubernetes)
- Model monitoring and drift detection
- Integration with big data tools (Spark, Hadoop)
- Real-time inference and batch prediction capabilities
- Explainable AI tools to interpret models
- Automated ML (AutoML) for rapid prototyping
- Custom algorithm development and optimization
- Scalable training on cloud GPUs/TPUs
- Security and privacy of training data
BUDGET
The estimated budget for this project ranges from 1,00,000 TO 2,00,000. However, the budget is flexible and can be adjusted based on the specific requirements and scope of the project to ensure the best possible outcome.