Valentina Porcu

Python for Data Mining Quick Syntax Reference (eBook, PDF)

• Format: PDF

Produktbeschreibung

¿Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You'll be introduced to several data mining packages, with examples of how to use each of them.

The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python's most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Apress
• Seitenzahl: 260
• Erscheinungstermin: 19. Dezember 2018
• Englisch
• ISBN-13: 9781484241134
• Artikelnr.: 56822706

Autorenporträt

Valentina Porcu is a computer geek with a passion for data mining and research, and a Ph.D in communication and complex systems. She has years of experience in teaching in universities in Italy, France and Morocco, and online, of course! She works as consultant in the field of data mining and machine learning and enjoys writing about new technologies and data mining. She spent the last 9 years working as freelancer and researcher in the field of social media analysis, benchmark analysis and web scraping for database building, in particular in the field of buzz analysis and sentiment analysis for universities, startups and web agencies across UK, France, US and Italy. Valentina is the founder of Datawiring, a popular Italian data science resource.

Inhaltsangabe

1. Getting Started.- 2. Introductory Notions.- 3. Basic Objects and Structures.- 4. Functions.- 5. Conditional Instructions and Writing Functions.- 6. Other Basic Concepts.- 7. Importing Files.- 8. pandas.- 9. SciPy and NumPy.- 10. Matplotlib.- 11. scikit-learn.