Machine Learning Data Lifecycle in Production

Por: Coursera . en: , ,

  • Week 1: Collecting, Labeling and Validating Data
    • This week covers a quick introduction to machine learning production systems. More concretely you will learn about leveraging the TensorFlow Extended (TFX) library to collect, label and validate data to make it production ready.
  • Week 2: Feature Engineering, Transformation and Selection
    • Implement feature engineering, transformation, and selection with TensorFlow Extended by encoding structured and unstructured data types and addressing class imbalances
  • Week 3: Data Journey and Data Storage
    • Understand the data journey over a production system’s lifecycle and leverage ML metadata and enterprise schemas to address quickly evolving data.
  • Week 4 (Optional): Advanced Labeling, Augmentation and Data Preprocessing
    • Combine labeled and unlabeled data to improve ML model accuracy and augment data to diversify your training set.