No-code ML with RapidMiner: Performing Regression Analysis

RapidMiner 9.9+    |    Intermediate
  • 16 videos | 1h 58m 9s
  • Includes Assessment
  • Earns a Badge
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Regression is used in the real world to predict things like stock prices, car mileage, or insurance premiums. RapidMiner studio offers an easy-to-use visual designer that allows you to construct a regression workflow with little to no code. In this course, explore regression models and the R-squared metric used to evaluate regression models. Next, use RapidMiner to retrieve data and use it for modeling. Then, automate data preparation with Turbo Prep, automate the training of multiple regression models using Auto Model, and compare these models using RapidMiner. Build a workflow to train regression models by using operators for data cleaning, imputing missing values, one-hot encoding, and partitioning your data. Finally, train multiple models for regression analysis and compare their performance and perform hyperparameter tuning to get the best model design for your use case. When you are finished with this course, you will be able to build a complete workflow in RapidMiner for regression analysis and improve your model using hyperparameter tuning.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Outline what regression is used for
    Load data into rapidminer and compute summary statistics
    View statistics on data
    Use univariate visualizations
    Use bivariate and multivariate visualizations
    Use the turbo prep tool for automating data preparation
    Use the auto model tool for automating machine learning
  • Perform data preparation and cleansing
    Remove highly correlated attributes
    Partition data for machine learning
    Encode data and select attributes
    Train a regression model
    Compare two different models
    Perform hyperparameter tuning
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 7s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 4m 52s
    After completing this video, you will be able to outline what regression is used for. FREE ACCESS
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    3.  Loading and Summarizing Data with RapidMiner
    5m 52s
    During this video, you will learn how to load data into RapidMiner and compute summary statistics. FREE ACCESS
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    4.  Computing Quality Measures and Statistical Summaries
    7m 27s
    In this video, discover how to view statistics on data. FREE ACCESS
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    5.  Visualizing Data with Univariate Visualizations
    9m 52s
    Upon completion of this video, you will be able to use univariate visualizations. FREE ACCESS
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    6.  Using Bivariate and Multivariate Visualizations
    9m 29s
    In this video, you will learn how to use bivariate and multivariate visualizations. FREE ACCESS
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    7.  Using Turbo Prep for Automated Data Preparation
    8m 57s
    Find out how to use the Turbo Prep tool for automating data preparation. FREE ACCESS
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    8.  Using Auto Model for Model Training and Evaluation
    10m 54s
    During this video, discover how to use the Auto Model tool for automating machine learning. FREE ACCESS
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    9.  Cleaning Data and Converting Types
    9m 28s
    After completing this video, you will be able to perform data preparation and cleansing. FREE ACCESS
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    10.  Computing and Filtering Correlated Attributes
    6m 37s
    In this video, find out how to remove highly correlated attributes. FREE ACCESS
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    11.  Creating Subprocesses and Partitioning Data
    4m 59s
    Discover how to partition data for machine learning. FREE ACCESS
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    12.  Selecting Attributes and One-hot Encoding
    6m 47s
    In this video, learn how to encode data and select attributes. FREE ACCESS
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    13.  Training a Linear Regression Model
    10m 17s
    During this video, discover how to train a regression model. FREE ACCESS
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    14.  Comparing Performance for Multiple Models
    7m 49s
    In this video, find out how to compare two different models. FREE ACCESS
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    15.  Tuning Random Forest Hyperparameters
    10m 35s
    Learn how to perform hyperparameter tuning. FREE ACCESS
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    16.  Course Summary
    2m 7s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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