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Nelli

Python Data Analytics: With Pandas, Numpy, and Matplotlib

Medium: Buch
ISBN: 978-1-4842-3912-4
Verlag: APRESS
Erscheinungstermin: 28.09.2018
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Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.

This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation
Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.
What You'll Learn - Understand the core concepts of data analysis and the Python ecosystem

- Go in depth with pandas for reading, writing, and processing data

- Use tools and techniques for data visualization and image analysis

- Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch

Who This Book Is For

Experienced Python developers who need to learn about Pythonic tools for data analysis


Produkteigenschaften


  • Artikelnummer: 9781484239124
  • Medium: Buch
  • ISBN: 978-1-4842-3912-4
  • Verlag: APRESS
  • Erscheinungstermin: 28.09.2018
  • Sprache(n): Englisch
  • Auflage: 2. Auflage 2018
  • Produktform: Kartoniert
  • Gewicht: 1098 g
  • Seiten: 569
  • Format (B x H x T): 178 x 254 x 31 mm
  • Ausgabetyp: Kein, Unbekannt
  • Vorauflage: 978-1-4842-0959-2
  • Nachauflage: 978-1-4842-9531-1
Autoren/Hrsg.

Autoren

Python Data Analytics

1. An Introduction to Data Analysis

2. Introduction to the Python's World

3. The NumPy Library

4. The pandas Library-- An Introduction

5. pandas: Reading and Writing Data

6. pandas in Depth: Data Manipulation

7. Data Visualization with matplotlib

8. Machine Learning with scikit-learn

9. Deep Learning with TensorFlow

10. An Example - Meteorological Data

11. Embedding the JavaScript D3 Library in IPython Notebook

12. Recognizing Handwritten Digits

13. Textual data Analysis with NLTK

14. Image Analysis and Computer Vision with OpenCV Appendix A Appendix B