Skip to main content

Introducing new learning courses and educational videos from Apress. Start watching

Spend

Abstract

I promised in the introduction to this book that if you built a foundation in pandas, you would be well positioned to dive into machine learning. I want to attempt to deliver on that promise.

Keywords

  • Dataframe
  • Cumsum
  • Forecasting Time Series Data
  • Prophet Class
  • Import Pandas

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-1-4842-3802-8_7
  • Chapter length: 7 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   34.99
Price excludes VAT (USA)
  • ISBN: 978-1-4842-3802-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   44.99
Price excludes VAT (USA)

Notes

  1. 1.

    http://scikit-learn.org/stable/index.html

  2. 2.

    https://github.com/dmlc/xgboost

  3. 3.

    https://github.com/facebook/prophet

  4. 4.

    https://github.com/facebook/prophet#installation-in-python

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and Permissions

Copyright information

© 2018 Max Humber

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Humber, M. (2018). Spend. In: Personal Finance with Python. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3802-8_7

Download citation