What's included

• Model Development and Training

  Design and implement machine learning models using PyTorch, ensuring high performance and accuracy. Utilize OpenCV for image processing tasks, enhancing model capabilities in computer vision applications.

• Data Preprocessing and Feature Engineering

  Perform data preprocessing, cleaning, and augmentation to prepare datasets for training. Develop and apply feature engineering techniques to improve model performance.

• Parallel and Distributed Computing

  Leverage multiprocessing techniques to optimize model training and inference times. Implement scalable solutions to handle large datasets and complex computations efficiently.

• Cloud Integration and Deployment

  Deploy and manage machine learning models on Microsoft Azure, ensuring robust, scalable, and secure solutions. Utilize Azure Machine Learning services for model training, validation, and deployment.

• Model Evaluation and Optimization

  Conduct rigorous testing and validation of models to ensure they meet performance and accuracy benchmarks. Optimize models for speed, efficiency, and scalability in production environments.

• Pipeline Development

  Develop end-to-end machine learning pipelines, from data ingestion to model deployment and monitoring. Automate workflows to streamline processes and enhance productivity.