UDEMY 2021 - End-to-end Machine Learning: Time-series analysis

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Build a weather predictor using python

You can find "Download Link" as a button at the end of this article.

What you’ll learn

  • Build a weather predictor using python.
  • Use autocorrelation to build time-series features.
  • Use autocorrelation to build time-series features.

  • Detect and remove seasonal trends.
  • Detect and remove seasonal trends.

  • Handle missing values.
  • Download and ingest csv-formatted data.
  • Handle dates in with a custom python converter.
  • Evaluate a time-series model’s performance.
  • Requirements

  • Some experience with python is helpful, but not required.
  • Description

    When you’re done, you’ll have a standalone weather predictor that can estimate high temperatures three days from now. You’ll also have hands-on experience solving a real word data science problem from end to end.

    If you are a professor or a teacher at any level, you are welcome to evaluate the course for free, and I can set your students up with a deep educational discount. Just contact me for the coupon code ([email protected]).

    Download File Here

    Who this course is for:

  • Machine learning students and data scientists seeking project-based time series modeling and autocorrelation instruction.
  • Created by Brandon RohrerLast updated 4/2018EnglishEnglish [Auto-generated]

    Size: 1.35 GB

    Download File Here


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