Model Trainer

Project MLOps for Orthographic Correction - SpellX

Version: v1.0.3

Release: Model Training

Features Added

• Model Training Module
  • Utilized the powerful Spello library for orthographic correction.
  • Trained a state-of-the-art model using high-quality labeled training data.
  • Implemented data preprocessing techniques to enhance model performance.

Data Preparation

• Carefully curated and validated training data to ensure its quality and correctness.
• Organized data into separate train, validation, and test sets within the data directory.

Model Training Details

• Leveraged Spello for training a robust orthographic correction model.
• Applied advanced machine learning techniques to improve model accuracy.
• Conducted extensive experimentation and fine-tuning to achieve superior results.

Version Control

• Maintained meticulous version information for both the training data and the trained model.
• Ensured traceability and reproducibility of the model training process.

Upcoming Enhancements

Future releases will continue to enhance the project's capabilities, including:

• Advanced data preprocessing techniques.
• Automated model training pipelines.
• Deployment and integration with real-time applications.
• Continuous improvement in model accuracy and performance.

Feedback

We value your feedback and suggestions as we strive to make our orthographic correction project even more effective and efficient. Please share your thoughts and insights to help us enhance our project further.

Stay tuned for further updates!

Data Validation

Project MLOps for Orthographic Correction - SpellX
Version: v1.0.1

Features:

• Data Validation Module
  • Establish a robust data validation process.
  • Ensure data integrity and consistency in the orthographic correction project.
  • Perform rigorous checks on the data collected from diverse sources.
  • Verify data quality and correctness through comprehensive validation procedures.
  • Organize data into separate train, validation, and test folders within the data directory.
  • Maintain version information for traceability and reproducibility.

Upcoming:

• Future releases will introduce advanced data preprocessing, model training, deployment pipelines, and more.

Feedback:

• We welcome your feedback and suggestions to enhance our project.

Stay tuned for further updates!

Data Ingestion

Project MLOps for Orthographic Correction - SpellX
Version: v1.0.0

Features:

• Data Ingestion Module
  • Set up a streamlined data ingestion pipeline.
  • Collect data from diverse sources for orthographic correction.
  • Preprocess ingested data for consistency and quality.
  • Store data efficiently in designated repositories.
  • Maintain version information for traceability and reproducibility.

Upcoming:

• Future releases will introduce advanced data preprocessing, model training, deployment pipelines, and more.

Feedback:

• We welcome your feedback and suggestions to enhance our project.

Stay tuned for further updates!