MLproject

name: stock_market_prediction_poc

conda_env: conda.yml

entry_points:
  download_raw_data:
    parameters:
      company_abbreviation: {type: string, default: MSFT}
    command: "python flow_steps/download_raw_data.py --company-abbreviation {company_abbreviation}"

  transform_data:
    parameters:
      dataset_stock_csv: path
      max_row_limit: {type: int, default: 100000}
    command: "python flow_steps/transform_data.py --dataset-stock-csv {dataset_stock_csv} --max-row-limit {max_row_limit}"

  train_model:
    parameters:
      stock_data: path
      lstm_units: {type: int, default: 50}
    command: "python flow_steps/train_model.py --stock-data {stock_data} --lstm-units {lstm_units}"

  deploy_model:
    parameters:
      model_dir: path
      bucket_name: {type: string, default: stock-market-models}
    command: "python flow_steps/deploy_model.py --model-dir {model_dir} --bucket-name {bucket_name}"

  main:
    parameters:
      lstm_units: {type: int, default: 50}
      max_row_limit: {type: int, default: 100000}
      company_abbreviation: {type: string, default: MSFT}
      bucket_name" {type:string, default: stock-market-models}
    command: "python main.py --lstm-units {lstm_units} --max-row-limit {max_row_limit} --company-abbreviation {company_abbreviation} --bucket-name {bucket_name}"