Using BigML: Getting Hands-on with BigML


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

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.



Expected Duration (hours)
1.3

Lesson Objectives

Using BigML: Getting Hands-on with BigML

  • 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
  • Course Number:
    it_damlubdj_02_enus

    Expertise Level
    Beginner