Practical Data Science with Python (eBook, ePUB) - George, Nathan
29,95 €
inkl. MwSt.
Sofort per Download lieferbar
payback
15 °P sammeln
  • Format: ePub

Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.
The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science.

The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion.

As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments.

By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source.

Autorenporträt
Nathan George is a data scientist at Tink in Stockholm, Sweden, and taught data science as a professor at Regis University in Denver, CO for over 4 years. Nathan has created online courses on Pythonic data science and uses Python data science tools for electroencephalography (EEG) research with the OpenBCI headset and public EEG data. His education includes the Galvanize data science immersive, a PhD from UCSB in Chemical Engineering, and a BS in Chemical Engineering from the Colorado School of Mines.