What are the perfect steps to follow to complete Data Science Project and Machine Learning with Deployment to Cloud

Data Science, AI and ML
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#1

What are the perfect steps to follow to complete Data Science Project and Machine Learning with Deployment to Cloud.

Example like -

  1. Checking Null values
  2. Outliers

Which steps comes when ?

#2

There are no rules for steps to solve a machine learning problem (order of different steps isnt imporatant…) still u may follow the below steps

  1. Data collection
  2. Data cleaning
    3)Feature Engg
    4)Train test slpit
    5)model fitting
  3. prediction
  4. Evaluation
  5. Deployment
    for more details go though this blog
    https://towardsdatascience.com/9-steps-for-solving-data-science-problems-dc3c238cb58c
    https://medium.com/cracking-the-data-science-interview/how-to-think-like-a-data-scientist-in-12-steps-157ea8ad5da8
#3

This is a bit strange starting point for a machine learning project. Usually you start with a problem to solve, and find data that can answer that problem, etc., but, if that’s how you roll, fine.

  • Given the two options you have, who are the target consumers of this machine learning model? Internal people, or external people?
  • How you get the data to power your machine learning model?
  • Can you use a standard vanilla algorithm or do you need to implement custom solution? Your vendor may not be able to support heavily customized solution.
  • How often do you need to update the model? - rewriting the model becomes a real headache if you need to update it often.