Source: dzone.com
How to Manage a Data Science Project for Successful DeliveryCategory: Deployment, Software, Business, Database, Data, machine-learning
Many practitioners believe that data science is serving their business efficiently. But many data science projects fail due to improper workflow while providing services to the customer.
In this article, we are giving a brief description of how you can manage a data science project for successful delivery. Before proceeding further, it is necessary to understand what a data science project is.
There are some problems facing the data scientist while working on a data science project, some described below: A problem statement in data science can be solved by following the following steps: Before you start a data science project, first you have to define your problem, which you will face in the project lifecycle.
In this article, we are giving a brief description of how you can manage a data science project for successful delivery. Before proceeding further, it is necessary to understand what a data science project is.
There are some problems facing the data scientist while working on a data science project, some described below: A problem statement in data science can be solved by following the following steps: Before you start a data science project, first you have to define your problem, which you will face in the project lifecycle.
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