Data Science is an interdisciplinary field that encompasses a variety of scientific procedures, algorithms, tools, and machine learning approaches that work together to uncover common patterns and gather useful insights from raw input data using statistical and mathematical analysis.
The following steps represents the life cycle of data science.
I. Business Understanding
For the problem that needs to be solved, ask pertinent questions and define objects.
II. Data Mining
Collect and scrape the data you'll need for the project.
III. Data Cleaning
Correct any inconsistencies in the data and deal with any missing values.
IV. Data Exploration
By visually evaluating the data, you can form hypotheses about your defined problem.
V. Feature Engineering
Choose the most significant qualities and use the raw data to create more meaningful ones.
VI. Predictive Modeling
Machine learning models can be trained, evaluated, and used to create predictions.
VII. Data Visualization
Plots and interactive visualization can be used to communicate the findings to important stakeholders.
