Time Series Forecasting in Python
Home > Computing and Information Technology > Databases > Data capture and analysis > Time Series Forecasting in Python
Time Series Forecasting in Python

Time Series Forecasting in Python

|
     0     
5
4
3
2
1




International Edition


About the Book

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In  Time Series Forecasting in Python  you will learn how to: Recognize a time series forecasting problem and build a performant predictive model Create univariate forecasting models that account for seasonal effects and external variables Build multivariate forecasting models to predict many time series at once Leverage large datasets by using deep learning for forecasting time series Automate the forecasting process DESCRIPTION  Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow.Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You'll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Time Series Forecasting in Python teaches you to build powerful predictive models from time-based data. Every model you create is relevant, useful, and easy to implement with Python. You'll explore interesting real-world datasets like Google's daily stock price and economic data for the USA, quickly progressing from the basics to developing large-scale models that use deep learning tools like TensorFlow. about the technology Time series forecasting reveals hidden trends and makes predictions about the future from your data. This powerful technique has proven incredibly valuable across multiple fields—from tracking business metrics, to healthcare and the sciences. Modern Python libraries and powerful deep learning tools have opened up new methods and utilities for making practical time series forecasts. about the book Time Series Forecasting in Python teaches you to apply time series forecasting and get immediate, meaningful predictions. You'll learn both traditional statistical and new deep learning models for time series forecasting, all fully illustrated with Python source code. Test your skills with hands-on projects for forecasting air travel, volume of drug prescriptions, and the earnings of Johnson & Johnson. By the time you're done, you'll be ready to build accurate and insightful forecasting models with tools from the Python ecosystem.

Table of Contents:
table of contents  detailed TOC PART 1: TIME WAITS FOR NO ONE READ IN LIVEBOOK 1UNDERSTANDING TIME SERIES FORECASTING READ IN LIVEBOOK 2A NAÏVE PREDICTION OF THE FUTURE READ IN LIVEBOOK 3GOING ON A RANDOM WALK PART 2: FORECASTING WITH STATISTICAL MODELS READ IN LIVEBOOK 4MODELING A MOVING AVERAGE PROCESS READ IN LIVEBOOK 5MODELING AN AUTOREGRESSIVE PROCESS READ IN LIVEBOOK 6MODELING COMPLEX TIME SERIES READ IN LIVEBOOK 7FORECASTING NON-STATIONARY TIME SERIES READ IN LIVEBOOK 8ACCOUNTING FOR SEASONALITY READ IN LIVEBOOK 9ADDING EXTERNAL VARIABLES TO OUR MODEL READ IN LIVEBOOK 10FORECASTING MULTIPLE TIME SERIES READ IN LIVEBOOK 11CAPSTONE: FORECASTING THE NUMBER OF ANTIDIABETIC DRUG PRESCRIPTIONS IN AUSTRALIA PART 3: LARGE-SCALE FORECASTING WITH DEEP LEARNING READ IN LIVEBOOK 12INTRODUCING DEEP LEARNING FOR TIME SERIES FORECASTING READ IN LIVEBOOK 13DATA WINDOWING AND CREATING BASELINES FOR DEEP LEARNING READ IN LIVEBOOK 14BABY STEPS WITH DEEP LEARNING READ IN LIVEBOOK 15REMEMBERING THE PAST WITH LSTM READ IN LIVEBOOK 16FILTERING OUR TIME SERIES WITH CNN READ IN LIVEBOOK 17USING PREDICTIONS TO MAKE MORE PREDICTIONS READ IN LIVEBOOK 18CAPSTONE: FORECASTING THE ELECTRIC POWER CONSUMPTION OF A HOUSEHOLD PART 4: AUTOMATING FORECASTING AT SCALE READ IN LIVEBOOK 19AUTOMATING TIME SERIES FORECASTING WITH PROPHET READ IN LIVEBOOK 20CAPSTONE: FORECASTING THE MONTHLY AVERAGE RETAIL PRICE OF STEAK IN CANADA 21 GOING ABOVE AND BEYOND APPENDIX APPENDIX A: INSTALLATION INSTRUCTIONS


Best Sellers


Product Details
  • ISBN-13: 9781617299889
  • Publisher: Manning Publications
  • Publisher Imprint: Manning Publications
  • Height: 234 mm
  • No of Pages: 456
  • Spine Width: 28 mm
  • Width: 186 mm
  • ISBN-10: 161729988X
  • Publisher Date: 10 Nov 2022
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Weight: 898 gr


Similar Products

Add Photo
Add Photo

Customer Reviews

REVIEWS      0     
Click Here To Be The First to Review this Product
Time Series Forecasting in Python
Manning Publications -
Time Series Forecasting in Python
Writing guidlines
We want to publish your review, so please:
  • keep your review on the product. Review's that defame author's character will be rejected.
  • Keep your review focused on the product.
  • Avoid writing about customer service. contact us instead if you have issue requiring immediate attention.
  • Refrain from mentioning competitors or the specific price you paid for the product.
  • Do not include any personally identifiable information, such as full names.

Time Series Forecasting in Python

Required fields are marked with *

Review Title*
Review
    Add Photo Add up to 6 photos
    Would you recommend this product to a friend?
    Tag this Book Read more
    Does your review contain spoilers?
    What type of reader best describes you?
    I agree to the terms & conditions
    You may receive emails regarding this submission. Any emails will include the ability to opt-out of future communications.

    CUSTOMER RATINGS AND REVIEWS AND QUESTIONS AND ANSWERS TERMS OF USE

    These Terms of Use govern your conduct associated with the Customer Ratings and Reviews and/or Questions and Answers service offered by Bookswagon (the "CRR Service").


    By submitting any content to Bookswagon, you guarantee that:
    • You are the sole author and owner of the intellectual property rights in the content;
    • All "moral rights" that you may have in such content have been voluntarily waived by you;
    • All content that you post is accurate;
    • You are at least 13 years old;
    • Use of the content you supply does not violate these Terms of Use and will not cause injury to any person or entity.
    You further agree that you may not submit any content:
    • That is known by you to be false, inaccurate or misleading;
    • That infringes any third party's copyright, patent, trademark, trade secret or other proprietary rights or rights of publicity or privacy;
    • That violates any law, statute, ordinance or regulation (including, but not limited to, those governing, consumer protection, unfair competition, anti-discrimination or false advertising);
    • That is, or may reasonably be considered to be, defamatory, libelous, hateful, racially or religiously biased or offensive, unlawfully threatening or unlawfully harassing to any individual, partnership or corporation;
    • For which you were compensated or granted any consideration by any unapproved third party;
    • That includes any information that references other websites, addresses, email addresses, contact information or phone numbers;
    • That contains any computer viruses, worms or other potentially damaging computer programs or files.
    You agree to indemnify and hold Bookswagon (and its officers, directors, agents, subsidiaries, joint ventures, employees and third-party service providers, including but not limited to Bazaarvoice, Inc.), harmless from all claims, demands, and damages (actual and consequential) of every kind and nature, known and unknown including reasonable attorneys' fees, arising out of a breach of your representations and warranties set forth above, or your violation of any law or the rights of a third party.


    For any content that you submit, you grant Bookswagon a perpetual, irrevocable, royalty-free, transferable right and license to use, copy, modify, delete in its entirety, adapt, publish, translate, create derivative works from and/or sell, transfer, and/or distribute such content and/or incorporate such content into any form, medium or technology throughout the world without compensation to you. Additionally,  Bookswagon may transfer or share any personal information that you submit with its third-party service providers, including but not limited to Bazaarvoice, Inc. in accordance with  Privacy Policy


    All content that you submit may be used at Bookswagon's sole discretion. Bookswagon reserves the right to change, condense, withhold publication, remove or delete any content on Bookswagon's website that Bookswagon deems, in its sole discretion, to violate the content guidelines or any other provision of these Terms of Use.  Bookswagon does not guarantee that you will have any recourse through Bookswagon to edit or delete any content you have submitted. Ratings and written comments are generally posted within two to four business days. However, Bookswagon reserves the right to remove or to refuse to post any submission to the extent authorized by law. You acknowledge that you, not Bookswagon, are responsible for the contents of your submission. None of the content that you submit shall be subject to any obligation of confidence on the part of Bookswagon, its agents, subsidiaries, affiliates, partners or third party service providers (including but not limited to Bazaarvoice, Inc.)and their respective directors, officers and employees.

    Accept

    New Arrivals

    Inspired by your browsing history


    Your review has been submitted!

    You've already reviewed this product!