Low-code ML with KNIME: Performing Time Series & Market Basket Analysis

KNIME 4.7+    |    Intermediate
  • 12 videos | 1h 25m 41s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 3 users Rating 4.3 of 3 users (3)
Organizations use time series analysis and market basket analysis to understand patterns over time. Time series analysis uses data collected over regular intervals to analyze how the variable changes over time, while market basket analysis is an application of association rule learning that tries to learn what items occur together frequently in the same transaction. In this course, discover how time series analysis works and how time series models like the autoregressive integrated moving average (ARIMA) model can help you forecast future values of time-varying data using historical values. Next, visualize time series data using moving averages and time series decomposition and fit an ARIMA model on this data for forecasting future values. Finally, use association rule learning for market basket analysis to analyze transaction data from a bakery and perform association rule learning on this data to figure out what items are frequently bought together. Upon course completion, you will be able to confidently use KNIME for time series analysis and market basket analysis.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline time series analysis
    Load data and convert string to date type
    Visualize data using moving averages
    Extract data from date fields
    Decompose time series signals
  • View and remove seasonality in time series data
    Perform time series forecasting using the autoregressive integrated moving average (arima) model
    Load data for market basket analysis
    Describe how association rules mining works
    Perform association rule learning for market basket analysis
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 56s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 7m 16s
    After completing this video, you will be able to outline time series analysis. FREE ACCESS
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    3.  Loading Data and Converting Date Types
    6m 32s
    During this video, discover how to load data and convert string to date type. FREE ACCESS
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    4.  Computing and Visualizing Moving Averages
    8m 1s
    In this video, find out how to visualize data using moving averages. FREE ACCESS
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    5.  Visualizing Data Quarterly and Monthly
    7m 16s
    Learn how to extract data from date fields. FREE ACCESS
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    6.  Decomposing Time Series Signals
    8m 40s
    In this video, discover how to decompose time series signals. FREE ACCESS
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    7.  Inspecting and Removing Seasonality
    7m 23s
    During this video, you will learn how to view and remove seasonality in time series data. FREE ACCESS
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    8.  Fitting an ARIMA (1, 1, 1) Model
    9m 3s
    Find out how to perform time series forecasting using the autoregressive integrated moving average (ARIMA) model. FREE ACCESS
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    9.  Loading and Preparing Data
    9m 23s
    In this video, learn how to load data for market basket analysis. FREE ACCESS
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    10.  Association Rules Learning
    7m 58s
    Discover how to describe how association rules mining works. FREE ACCESS
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    11.  Performing Association Rule Learning
    9m 34s
    In this video, find out how to perform association rule learning for market basket analysis. FREE ACCESS
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    12.  Course Summary
    2m 41s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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