CODEWITHSUNDEEP
apache-sparkmachine-learning
Appala
Appala

Reputation: 41

Steps to deploy trained machine leaning model into production

I am new to ML world, when reading about building model with training data and finally test the data to suit requirements, till this point I am able to follow, my questions is once tested model is ready to deply

  1. Do I need to train / re-train the model after production deployment? if so what is the practice?
  2. Is there way to persists the hypothesis, so that model can predict using result which are persisted?
  3. Is it good practice to re-train the model every day or week or month?

Assuming spark MLib is used to build the model

I am very new to machine learning, would like to understand how model code released to next environment, what steps I need to consider

thanks for clarification, which means I need to deploy model object into production then use production data (features) to calculate target data value?, can you please refer me to any book or information where I can get inside into how to build, validate and deploy supervised algorithms.

again, thanks for your time to educate me.

Upvotes: 1

Views: 250

Answers (1)

screechOwl
screechOwl

Reputation: 28169

Do I need to train / re-train the model after production deployment? if so what is the practice?

Not necessarily but you probably will. A lot depends on what's being modeled and how stable it is over time.

Is there way to persists the hypothesis, so that model can predict using result which are persisted?

  • ?? Not sure I understand the question but most production models have logging systems attached to analysis / reporting / vizualization software to help keep track of model performance and help decide when to retrain.

Is it good practice to re-train the model every day or week or month?

  • Kind of depends on performance and resource constraints. If you have a small number of models to retrain / score with and retraining won't affect SLA's, it's probably not a bad idea but when there are limited computing resources the answer might change.

Upvotes: 1

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