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Time Series Analysis with Python 3.x
Time Series Analysis with Python 3.x

Time Series Analysis with Python 3.x: Effectively utilize Python and NumPy for time series analysis

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Profile Icon Karen Yang
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€103.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Jan 2020 3hrs 23mins 1st Edition
Video
€103.99
Subscription
Free Trial
Renews at €18.99p/m
Arrow left icon
Profile Icon Karen Yang
Arrow right icon
€103.99
Full star icon Full star icon Full star icon Full star icon Full star icon 5 (1 Ratings)
Video Jan 2020 3hrs 23mins 1st Edition
Video
€103.99
Subscription
Free Trial
Renews at €18.99p/m
Video
€103.99
Subscription
Free Trial
Renews at €18.99p/m

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Key benefits

  • Perform efficient time series analysis using Python and master essential machine learning models
  • Apply various time series methods and techniques and assemble a project step-by-step
  • Build a complete project on anomaly detection that has a distinct emphasis on applications in the finance (or any other) domain

Description

Time series analysis encompasses methods for examining time series data found in a wide variety of domains. Being equipped to work with time-series data is a crucial skill for data scientists. In this course, you'll learn to extract and visualize meaningful statistics from time series data. You'll apply several analysis methods to your project. Along the way, you'll learn to explore, analyze, and predict time series data. You'll start by working with pandas' datetime and finding useful ways to extract data. Then you'll be introduced to correlation/autocorrelation time-series relationships and detecting anomalies. You'll learn about autoregressive (AR) models and Moving Average (MA) models for time series, and explore anomalies in detail. You'll also discover how to blend AR and MA models to build a robust ARMA model. You'll also grasp how to build time series forecasting models using ARIMA. Finally, you'll complete your own project on time series anomaly detection. By the end of this practical tutorial, you'll have acquired the skills you need to perform time series analysis using Python. Please note that this course assumes some prior knowledge of Python programming; a working knowledge of pandas and NumPy; and some experience working with data. The code bundle for this course is available at https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-3.x

Who is this book for?

This course is for anyone interested in time-based data who has a working knowledge of pandas and NumPy. If you are a Python developer and want to conduct analysis based on time series data, then this course is for you.

What you will learn

  • Key pandas concepts and techniques for time-based analysis
  • Study and work with important components of time series data such as trends, seasonality, and noise
  • Apply commonly used machine learning models for analysis
  • How to de-trend and de-seasonlize time series data
  • Manipulate data with AR, MA, and ARMA
  • Decompose time series data into its components for efficient analysis
  • Create an end-to-end anomaly detection project based on time series

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jan 23, 2020
Length: 3hrs 23mins
Edition : 1st
Language : English
ISBN-13 : 9781838640590
Category :
Languages :
Concepts :
Tools :

What do you get with a video?

Product feature icon Download this video in MP4 format
Product feature icon Access this title in our online reader with advanced features
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Jan 23, 2020
Length: 3hrs 23mins
Edition : 1st
Language : English
ISBN-13 : 9781838640590
Category :
Languages :
Concepts :
Tools :

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Frequently bought together


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Time Series Analysis with Python 3.x
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Table of Contents

5 Chapters
Setting Up and Learning Ways to Get Data Chevron down icon Chevron up icon
Time Series Data and Relationships Chevron down icon Chevron up icon
Operating with Time Series Models Chevron down icon Chevron up icon
Working with Various ML Models for Time Series Analysis Chevron down icon Chevron up icon
Completing Your Project on Anomaly Detection Chevron down icon Chevron up icon

Customer reviews

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Carlo Estopia Feb 18, 2024
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