Using BigML: Getting Hands-on with BigML

Machine Learning    |    Beginner
  • 11 videos | 1h 16m 26s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 26 users Rating 4.3 of 26 users (26)
BigML not only provides ease-of-use, but it also offers flexibility in how you work with your data. This course serves as a hands-on introduction to BigML and its vast array of features. You'll start by exploring the different ways data can be loaded into the platform and how these can be transformed into datasets to train and test a machine learning model. You'll gain practical experience with some of the tools available to help you better understand your data - from histograms and scatterplots to visualizations of value distribution. Moving on, you'll build a fundamental classification model, a decision tree, which takes employee details and predicts whether they'll stay or leave in the next year. Finally, you'll investigate some possible configurations for this model.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Recognize the features available in bigml to load data and train a machine learning model
    Load data from a variety of sources into bigml in order to train and evaluate machine learning models
    Organize your bigml resources into projects, such as data sources, datasets, and models
    Create a dataset out of a data source and analyze the different fields in the data
    Visualize relationships between various fields in a dataset
  • Split and sample a dataset, which can then be used to train and test a model
    Build a classification model that uses a decision tree and recognize how this performs classification
    Illustrate the process involved in performing classification when a decision tree model is used
    Customize a decision tree model when performing classification
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 2m 32s
  • 8m 32s
    Upon completion of this video, you will be able to recognize the features available in BigML to load data and train a machine learning model. FREE ACCESS
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    3.  Loading Data into BigML
    8m 2s
    During this video, you will learn how to load data from a variety of sources into BigML in order to train and evaluate machine learning models. FREE ACCESS
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    4.  Creating a Project from BigML Resources
    9m
    In this video, you will learn how to organize your BigML resources into projects, such as data sources, datasets, and models. FREE ACCESS
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    5.  Creating and Analyzing Datasets
    8m 45s
    Find out how to create a dataset from a data source and analyze the different fields in the data. FREE ACCESS
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    6.  Examining Relationships in Datasets
    9m 21s
    In this video, you will learn how to visualize relationships between various fields in a dataset. FREE ACCESS
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    7.  Transforming a Dataset
    7m 48s
    In this video, you will learn how to split and sample a dataset, which can then be used to train and test a model. FREE ACCESS
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    8.  Building a Decision Tree Model
    8m 44s
    In this video, you will build a classification model that uses a decision tree and recognize how this performs classification. FREE ACCESS
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    9.  Analyzing a Decision Tree
    5m 58s
    Upon completion of this video, you will be able to illustrate the process involved in performing classification when a decision tree model is used. FREE ACCESS
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    10.  Configuring a Decision Tree
    6m 9s
    During this video, you will learn how to customize a decision tree model for classification. FREE ACCESS
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    11.  Course Summary
    1m 37s

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