Practical Data Science with Jupyter: Explore Data Cleaning, Pre-processing, Data Wrangling, Feature Engineering (True EPUB)

Solve business problems with data-driven techniques and easy-to-follow Python examples
KEY FEATURES
● Essential coverage on statistics and data science techniques.
● Exposure to Jupyter, PyCharm, and use of GitHub.
● Real use-cases, best practices, and smart techniques on the use of data science for data applications.
DESCRIPTION
This book begins with an introduction to Data Science followed by the Python concepts. The readers will understand how to interact with various database and Statistics concepts with their Python implementations. You will learn how to import various types of data in Python, which is the first step of the data analysis process. Once you become comfortable with data importing, you will clean the dataset and after that will gain an understanding about various visualization charts. This book focuses on how to apply feature engineering...