Predictive Analytics: Performing Classification Using Machine Learning

Predictive Analytics    |    Intermediate
  • 13 videos | 1h 21m 58s
  • Includes Assessment
  • Earns a Badge
Rating 4.7 of 6 users Rating 4.7 of 6 users (6)
Species identification is an important step in many agricultural processes. With supply chain globalization and strict grading norms imposed by importing nations on the composition of consignments, machine learning (ML) techniques geared towards classification are becoming increasingly relevant in agriculture. In this course, learn how to perform exploratory data analysis on data about beans. Next, discover how to visualize the data to get a sense of the relationships between the attributes, perform logistic regression to classify the beans, and explore the result metrics of the model. Finally, practice performing feature selection and using other types of machine learning models. Upon completion, you'll be able to analyze agricultural data, recognize relationships between attributes, and classify data based on type.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Create an azure machine learning workspace
    Use azure machine learning
    Read in data to pandas data frames and explore the data
    Visualize data attributes
    View attribute relationships in the data
    Set up data for performing classification
  • Classify types using machine learning (ml)
    Select the most important attributes for classification
    Perform feature selection for classification
    Set up a classifier
    Classify data by type using machine learning models
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 22s
  • 3m 27s
  • Locked
    3.  Using Azure Machine Learning
    7m 59s
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    4.  Reading in Data Using pandas
    6m 33s
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    5.  Visualizing Data Attributes
    6m 10s
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    6.  Viewing Attribute Relationships
    6m 31s
  • Locked
    7.  Setting Up Data for Classification
    7m 8s
  • Locked
    8.  Classifying Types Using Machine Learning
    8m 34s
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    9.  Selecting Important Attributes for Classification
    9m 40s
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    10.  Performing Feature Selection for Classification
    7m 29s
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    11.  Setting Up a Classifier
    7m 16s
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    12.  Classifying by Type
    6m 45s
  • Locked
    13.  Course Summary
    3m 5s

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