Data exploration and analysis is at the core of data science. Data scientists require skills in programming languages like Python to explore, visualize, and manipulate data.
In this module, you will learn:
Common data exploration and analysis tasks. How to use Python packages like NumPy, Pandas, and Matplotlib to analyze data.
In this module, you learned how to use Python to explore, visualize, and manipulate data. Data exploration is at the core of data science and is a key element in data analysis and machine learning.
Machine learning is a subset of data science that deals with predictive modeling. In other words, machine learning uses data to create predictive models in order to predict unknown values. You might use machine learning to predict how much food a supermarket needs to order or to identify plants in photographs.
Machine learning works by identifying relationships between data values that describe the characteristics of something (its features—such as the height and color of a plant) and the value we want to predict (the label—such as the species of plant). These relationships are built into a model through a training process.