/TFX--End-to-End--Pipeline-for-US-Salary-Prediction

US Salary Prediction Repository Demonstrate end-to-end workflow implementation using TFX

Primary LanguageJupyter Notebook

TFX--End-to-End--Pipeline-for-US-Salary-Prediction

US Salary Prediction Repository Demonstrate end-to-end workflow implementation using TFX

Following Components were used

  • ExampleGen - ingests and splits the input dataset.
  • StatisticsGen - calculates statistics for the dataset.
  • SchemaGen - examines the statistics and creates a data schema.
  • ExampleValidator - looks for anomalies and missing values in the dataset.
  • Transform performs - feature engineering on the dataset.
  • Trainer - trains the model using TensorFlow Estimators or Keras.
  • Evaluator - performs deep analysis of the training results.
  • Pusher - deploys the model to a serving infrastructure.

Tensorflow serving is used for the deployement