This website provides access to downloading an open source machine learning and data visualization desktop application appropriate for novices as well as useful for experts. The application addresses interactive data analysis workflows and includes an externsive toolbox.
Type of Material:
Development Tool, Support Videos, and Lecture Notes
Recommended Uses:
This tool is best used as support for a course and is appropriate for both in-person and online courses.
Technical Requirements:
Tool requires Microsoft Windows, Apple OS X, LInux, and/or appropriate installation of Python.
Identify Major Learning Goals:
Simple data analysis with data visualization
Visualization and manipulation of statistical distributions
Interactive data exploration
Target Student Population:
College General Ed, College Lower Division, College Upper Division, Graduate School
Prerequisite Knowledge or Skills:
Background knowledge of data science and data mining.
Fundamentals of computing, information representation, andprogramming.
Mathematical underpinnings in statistics and data science.
Content Quality
Rating:
Strengths:
This tool is useful for teaching data mining in particular and machine learning in general.
It provides comprehensive features for students to explore data mining and to conduct data analysis.
The content is of high quality with good documentation.
In includes the followings:
Addresses common data workflows
Extensive collection of data manipulation and visualization tools
Appropriate for data science and data mining coursework
Approach is appropriate for students in associated courses
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
Documentation articulates learning goals and provides links to associated resources
Use of YouTube tutorials and visualization components increases engagement and thus the potential for student learning
Inclusion of workflow examples and extensive catalog of workflow components, in conjunction with tutorials, promotes conceptual understanding
The application affords use in live demonstrations and both self-directed and guided explorations to achieve learning goals
It can be used in lectures and projects. For example, various machine learning models can be demonstrated and tested through a graphical interface.
The tool can facilitate the learning of data mining and it reinforces concept understanding (e.g., through hands on experience).
The learning goals are clear and the tool can enhance student learning in various aspects.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
Ample instructions are provided for accessing, installing, and using the application
The website provides a clear and consistent layout
The website is easy to navigate
The website is in working order
The software appears to be stable and maintained
Concerns:
The complexity of the interface may be an impediment to new users. Such complexity may be inherent in the current state of the domain and the application does appear to increase the accessibility of the underlying tools.
Some interaction with the software may not yet be fully implemented (as of version 3.24.1); for example, the message, "There is no documentation for this widget."
Creative Commons:
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