Unscrambler tutorials

Get familiar with different functions in Unscrambler, and then put what you learn into practice to analyse your own data. New videos will be added covering more features and feedback from users.

Unscrambler Tutorial

Data import

This video describes how data is easily imported into Unscrambler. Examples for import of an Excel file and a proprietary format for spectral data are shown.

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Unscrambler Tutorial

Preprocessing and transforms

Several methods for typical preprocessing procedures, such as correction for baseline offset and scatter, can be easily performed in Unscrambler.

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Unscrambler Tutorial

Building a PLS model

This video shows how to perform partial least squares (PLS) regression (PLS) to build models for predicting one or more properties of interest (dependent variable Y) based on multiple predictor variables (independent variable X).

WATCH VIDEO

Unscrambler Tutorial

Data handling

Learn about useful tips for organising your data before analysis, from creating subsets of data within a table (row and column ranges) and changing variable types (numeric, category, text…) to editing values for cells and defining data as spectra.

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Unscrambler Tutorial

Building a PCA model

Often called the work horse of multivariate analysis methods, Principal Component Analysis (PCA) simplifies data by reducing it to only a few dimensions, thereby easing interpretation.

WATCH VIDEO

Unscrambler Tutorial

Interpreting a PLS model

Learn how to interpret results of partial least squares (PLS) regression, including tools for assessing how well the model works for predicting the property/properties of interest, Y.

WATCH VIDEO

Unscrambler Tutorial

Diagnostics and plotting

Several plotting routines to visualise data are available from Unscrambler with just a few clicks. Other diagnostic tools available include univariate descriptive statistics (mean, standard deviation, box plot,…) and tools to assess scatter effects in spectral data.

WATCH VIDEO

Unscrambler Tutorial

Interpreting a PCA model

Learn how to interpret the main results of a PCA analysis including the scores plot to understand relationships between samples, the loadings plot to understand relationships between variables, and combining both to relate samples with variables.

WATCH VIDEO

Python tutorials

Get started using Python scripts in Unscrambler, and learn the basics of how to prepare data, run scripts and visualise the results.

Python Tutorial

Installing Python

This video shows how to download and install Python in your windows system. You need to have a Python installation (version 3.7 or higher) to run Python scripts in Unscrambler.

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Python Tutorial

Installing Python packages

Separate Python packages or libraries may be required to run certain Python scripts (dependencies). This video shows how to install Python packages.

WATCH VIDEO

Python Tutorial

Running advanced Python scripts in Unscrambler

Learn how to set up new Python scripts as configurations to run from within Unscrambler.

WATCH VIDEO

Python Tutorial

Installing the PyCamo package

The PyCamo Python package facilitates the connection between Unscrambler and Python. Watch this video to learn how to set it up.

WATCH VIDEO

Python Tutorial

Data Import and preparation for Python scripting

This video shows how to import and organise data in Unscrambler.

WATCH VIDEO

Python Tutorial

Visualising Python script results in Unscrambler

See how outputs from Python scripts can be easily visualised and interpreted using the exploratory approach in Unscrambler.

WATCH VIDEO

Python Tutorial

Running a simple Python script

This video shows how to run a simple Python script from Unscrambler. The script shown comes pre-installed with Unscrambler 11, and its purpose is to verify the Unscrambler-Python installation.

WATCH VIDEO

Python Tutorial

Getting Python scripts from Camo Community

Example Python scripts for import and export, plotting and machine learning are available from Camo Community. This video shows how to download a script to perform t-SNE, a machine learning algorithm.

WATCH VIDEO

Check out our YouTube channel for more videos.

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Unscrambler tutorials

Get familiar with different functions in Unscrambler, and then put what you learn into practice to analyse your own data. New videos will be added covering more features and feedback from users.

Unscrambler Tutorial

Data import

This video describes how data is easily imported into Unscrambler. Examples for import of an Excel file and a proprietary format for spectral data are shown.

Unscrambler Tutorial

Preprocessing and transforms

Several methods for typical preprocessing procedures, such as correction for baseline offset and scatter, can be easily performed in Unscrambler.

Unscrambler Tutorial

Building a PLS model

This video shows how to perform partial least squares (PLS) regression (PLS) to build models for predicting one or more properties of interest (dependent variable Y) based on multiple predictor variables (independent variable X).

Unscrambler Tutorial

Data handling

Learn about useful tips for organising your data before analysis, from creating subsets of data within a table (row and column ranges) and changing variable types (numeric, category, text…) to editing values for cells and defining data as spectra.

Unscrambler Tutorial

Building a PCA model

Often called the work horse of multivariate analysis methods, Principal Component Analysis (PCA) simplifies data by reducing it to only a few dimensions, thereby easing interpretation.

Unscrambler Tutorial

Interpreting a PLS model

Learn how to interpret results of partial least squares (PLS) regression, including tools for assessing how well the model works for predicting the property/properties of interest, Y.

Unscrambler Tutorial

Diagnostics and plotting

Several plotting routines to visualise data are available from Unscrambler with just a few clicks. Other diagnostic tools available include univariate descriptive statistics (mean, standard deviation, box plot,…) and tools to assess scatter effects in spectral data.

Unscrambler Tutorial

Interpreting a PCA model

Learn how to interpret the main results of a PCA analysis including the scores plot to understand relationships between samples, the loadings plot to understand relationships between variables, and combining both to relate samples with variables.

Python tutorials

Get started using Python scripts in Unscrambler, and learn the basics of how to prepare data, run scripts and visualise the results.

Python Tutorial

Installing Python

This video shows how to download and install Python in your windows system. You need to have a Python installation (version 3.7 or higher) to run Python scripts in Unscrambler.

Python Tutorial

Installing Python packages

Separate Python packages or libraries may be required to run certain Python scripts (dependencies). This video shows how to install Python packages.

Python Tutorial

Running advanced Python scripts in Unscrambler

Learn how to set up new Python scripts as configurations to run from within Unscrambler.

Python Tutorial

Installing the PyCamo package

The PyCamo Python package facilitates the connection between Unscrambler and Python. Watch this video to learn how to set it up.

Python Tutorial

Data Import and preparation for Python scripting

This video shows how to import and organise data in Unscrambler.

Python Tutorial

Visualising Python script results in Unscrambler

See how outputs from Python scripts can be easily visualised and interpreted using the exploratory approach in Unscrambler.

Python Tutorial

Running a simple Python script

This video shows how to run a simple Python script from Unscrambler. The script shown comes pre-installed with Unscrambler 11, and its purpose is to verify the Unscrambler-Python installation.

Python Tutorial

Getting Python scripts from Camo Community

Example Python scripts for import and export, plotting and machine learning are available from Camo Community. This video shows how to download a script to perform t-SNE, a machine learning algorithm.

Check out our YouTube channel for more videos.