A Step By Step Guide To AI Model Development - Deepstash
AI adoption

In 2019, near 87% of data science projects did not get into production. However, due to COVID -19, most companies have scaled up their AI adoption and increased their AI investment.

In 2020, ...

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A Step By Step Guide To AI Model Development

datasciencecentral.com

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AI model development involves multiple stages that interconnect to each other.

  1. Identify the business problem. Instead of asking how to improve your...

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Define the business problem you are trying to solve.

  • What results are you expecting from the process?
  • What processes are used to solve this...

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Ask questions, such as.

  • What data is needed to solve the business problem?
  • What quantity of data is required?
  • Do you have enough data to bu...

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This step is the most time-consuming, with ML engineers spending around 80% of the AI model development time in this stage. A significant amount of time is spent cleaning the data and transforming ...

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At this step, all the requirements have been collected for the solution modelling to proceed.

ML engineers will define the features of the model, taking the following into account:

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While the model is trained and tuned using the training and validation data set, the model will behave differently when used in the real world, which is fine.

The main objective is to

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Analyse if the KPIs and the business objective of the model are achieved. If the parameters are not met, consider changing the model or improving the quality and quantity of the data.

Bef...

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