Low-code ML with KNIME: Building Regression Models

KNIME 4.7+    |    Intermediate
  • 15 videos | 1h 35m 33s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 6 users Rating 4.7 of 6 users (6)
Regression analysis is used to predict continuous data values. The KNIME Analytics Platform allows you to load, explore, pre-process, and use data to train regression models with little to no code. Through this course, learn how to train and evaluate regression models in KNIME. Explore how regression models work and use KNIME nodes to build a workflow to load and comprehend data. Next, discover how to compute correlations and use bar charts, box plots, scatter plots, and pivot tables. Finally, learn how to pre-process flight prediction data using one-hot and label encoding, partition data, and train regression models. After course completion, you'll be able to build a complete workflow in KNIME for regression analysis.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Recognize how regression models work
    Import csv data and compute summary statistics
    View data statistics and visualizations and compute correlations between attributes
    Analyze fields using histograms
    Use univariate bar charts and box plots
    Set up and use bivariate bar charts
    Visualize bivariate data using scatter plots
  • Create a bar chart using pivot table data
    Visualize aggregated data in scatter plots
    Create and use workflow annotations
    Perform one-hot and label encoding
    Use linear regression models for machine learning
    Use gradient boosting models for machine learning
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 32s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 57s
    After completing this video, you will be able to recognize how regression models work. FREE ACCESS
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    3.  Reading in Data and Computing Summary Statistics
    8m 51s
    In this video, you will learn how to import CSV data and compute summary statistics. FREE ACCESS
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    4.  Viewing Statistics and Computing Correlations
    8m 35s
    Find out how to view data statistics and visualizations and compute correlations between attributes. FREE ACCESS
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    5.  Analyzing Fields Using Histograms
    5m 44s
    In this video, discover how to analyze fields using histograms. FREE ACCESS
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    6.  Using Univariate Bar Charts and Box Plots
    8m 21s
    Learn how to use univariate bar charts and box plots. FREE ACCESS
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    7.  Setting Up a Multivariate Bar Chart
    4m 56s
    In this video, find out how to set up and use bivariate bar charts. FREE ACCESS
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    8.  Using Scatter Plots for Multivariate Analysis
    4m 4s
    Discover how to visualize bivariate data using scatter plots. FREE ACCESS
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    9.  Pivoting and Visualizing Data
    8m 22s
    During this video, you will learn how to create a bar chart using pivot table data. FREE ACCESS
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    10.  Visualizing Aggregated Scatter Plots
    7m 25s
    In this video, find out how to visualize aggregated data in scatter plots. FREE ACCESS
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    11.  Annotating Workflows
    3m 7s
    During this video, discover how to create and use workflow annotations. FREE ACCESS
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    12.  Performing One-Hot and Label Encoding
    9m 20s
    In this video, you will learn how to perform one-hot and label encoding. FREE ACCESS
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    13.  Training and Evaluating a Linear Regression Model
    10m 23s
    Find out how to use linear regression models for machine learning. FREE ACCESS
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    14.  Using Gradient Boosting Models for Machine Learning
    8m 7s
    In this video, discover how to use gradient boosting models for machine learning. FREE ACCESS
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    15.  Course Summary
    1m 49s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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