Application of Data Science
As mentioned in the introduction, data science is a multidisciplinary approach to analyzing and identifying complex patterns and extracting valuable insights from data. Running a data science project usually involves multiple steps, including the following:
- Defining the business problem to be solved
- Collecting or extracting existing data
- Analyzing, visualizing, and preparing data
- Training a model to spot patterns in data and make predictions
- Assessing a model's performance and making improvements
- Communicating and presenting findings and gained insights
- Deploying and maintaining a model
As its name implies, data science projects require data, but it is actually more important to have defined a clear business problem to solve first. If it's not framed correctly, a project may lead to incorrect results as you may have used the wrong information, not prepared the data properly, or led a model to learn the...
