Resource Library

Weight of Evidence Node in Altair® Knowledge Studio®

Knowledge Studio’s Weight of Evidence node is essential to creating scorecard models. The Weight of Evidence node transforms your data so the model can assign points to every bin and these points will eventually add up to the scorecard. Knowledge ...

How-to

Machine Learning 101 Part 2: Supervised Versus Unsupervised Learning

This is part two in a series of short videos to help you understand the basics of data science. This video focuses on the concepts of supervised and unsupervised learning. In supervised learning, you develop algorithms that predict outcomes based ...

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Machine Learning 101 Part 3: Prescriptive Analytics

This is part three in a series of short videos to help you understand the basics of data science. This video focuses on prescriptive analytics, which uses results from multiple machine learning algorithms to inform future decisions. With prescript...

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Machine Learning 101 Part 1: Predictive Analytics

This series of short videos will help you understand the basics of data science. In Part 1, we focus on predictive analytics, which is the process of training computers with historical data so they can make accurate predictions.

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How-to

Use Altair Knowledge Studio's XGB Node in Predictive Modeling Applications

XGB stands for “eXtreme Gradient Boosting” and is often referred to as XGBoost. Knowledge Studio includes an XGB node for predictive modeling that data scientists can use to develop solutions for classification and regression problems. Knowledge S...

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Detect Anomalies and Outliers with Altair Knowledge Studio

Knowledge Studio’s novelty and outlier detector node makes it easy to identify anomalies in a dataset and remove them if desired. The software supports three different methods for detecting outliers: Isolation Forest, Local Outlier Factor, and One...

How-to

Analyze Shapley Values with Altair® Knowledge Studio®

Knowledge Studio supports analysis of Shapley values, a solution concept from the world of cooperative game theory. Data scientists can use Shapley values to explain individual predictions of black box machine learning models, including random for...

How-to

Build Autoregressive Integrated Moving Average (ARIMA) Machine Learning Models in Altair® Knowledge Studio®

Knowledge Studio supports Autoregressive Integrated Moving Average (ARIMA) models, a powerful way to make accurate predictions based on time series data. You can add ARIMA models to your AI workflows with a fully menu-driven user interface. The so...

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Develop Connected Product Ecosystems with Altair® SmartWorks® IoT

Explore how SmartWorks IoT helps a high-end electric motorcycle company develop an application to manage its fleet of motorcycles. See how the manufacturer plans to provide its users, including individual owners, rental companies, and servicing fi...

How-to

Named Filters in Altair® Monarch®

Monarch Data Prep Studio makes it easy to create formula-based, value-based, or compound filters that you can apply to defined tables on the fly. You can also export data with filters applied to facilitate downstream analysis of selected subsets of data.

This video shows you how to build, name,

How-to

Create Ad-hoc Tables from PDF Documents in Altair® Monarch®

Monarch lets you define ad-hoc tables using data in PDF documents that is not presented in tabular forms. This video shows you how to use the Create New Ad-hoc Table function of the PDF Table Extractor in Monarch Data Prep Studio.

How-to

Automatically Capture Data from Tables in PDF Documents with Altair® Monarch®

Monarch’s table extraction function is designed for ordinary people who wish to do extraordinary things with PDF files. It enables business users to identify tables in text-heavy PDF files, select them, modify them as needed, and export the data t...

How-to

Create Custom Data Cleansing Macros in Altair® Monarch®

Monarch Data Prep Studio allows you to create macros that combine a series of data prep functions into a single step and then apply all the functions in the macro to multiple columns and tables and across workspaces.

This video shows you how to build, manage, and share macros in Monarch Data Pre

How-to

Import Tables from PDF Table Extractor into Altair® Monarch ® Data Prep Studio

After you have defined a set of tables for a PDF document with Monarch’s PDF Table Extractor, you can load the tables into Monarch Data Prep Studio for blending, transformation, and analysis.

This video shows you how to import tables from PDF Table Extractor into Monarch Data Prep Studio.

How-to

Manually Capture Data from Tables in PDF Documents using Altair® Monarch®

Monarch’s Create Table from Selection function makes it easy to capture data from just one section of a table within a PDF document. You can create a new table using only the highlighted rows and columns in an existing table and append data to an existing table.

This short video shows you how to

How-to

Modify Tables Extracted from PDF Documents with Altair® Monarch®

PDF Table Extractor allows you to modify and tweak a table definition as needed. You can define new tables, create new columns, delete columns, define table titles, modify headers, and more.

This video shows you how to modify tables in Monarch Data Prep Studio’s PDF Table Extractor.

How-to

Substitute Missing Values in Altair Knowledge Studio

Datasets often have missing values due to file corruption, failure to record data points, or other causes. Handling missing data values correctly is critical to developing accurate predictive models. Knowledge Studio makes it easy to identify data...

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Detect Simpson’s Paradox with Altair® Knowledge Studio®

In simple terms, Simpson’s Paradox occurs when a trend appears in subgroups but disappears or is reversed when subgroups are combined into a single dataset. Knowledge Studio supports detection of this statistical phenomenon. In this video, you wil...

How-to

Working with Imbalanced Classes in Altair® Knowledge Studio®

Most machine learning algorithms assume there are equal numbers of examples for each class in the source data. Many datasets contain substantially different numbers of records for important classes — resulting in an imbalanced class problem. Failu...

How-to

Using the Generalized Linear Model (GLM) Node in Altair® Knowledge Studio®

In the context of machine learning applications, GLM models allows the use of dependent variables that do not follow normal distributions. This video shows how easy it is to use Knowledge Studio’s GLM node to utilize this advanced statistical tech...

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Ziegler PEM Material Database

Altair has partnered with Ziegler-Instruments to enhance its Squeak and Rattle Director (SnRD), making it the most advanced and comprehensive solution on the market to predict and eradicate squeak and rattle phenomena in vehicles, aircraft and oth...

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Altair Inspire Optimization Workflow

This series of videos shows users how to use Altair Inspire from start to finish. Examples include defining the design space, analyzing dynamic motion, conducting topology optimization studies, designing for additive manufacturing, verifying desig...

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Optimize Manufacturability with Altair Inspire Print3D

Design for additive manufacturing with overhang shape controls to help reduce overhangs to create more self-supporting structures.

How-to

Dynamic Motion Analysis in Altair Inspire

Easily generate dynamic motion of complex mechanisms, automatically identifying contacts, joints, springs, and dampers.

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Fatigue Analysis in SimSolid 2020.2

The latest release of Altair SimSolid adds support for an integrated, two-step fatigue assessment. The highly automated workflow allows to setup and run a fatigue analysis with multiple load cases literally in seconds.

How-to

Verify Final Designs in Altair Inspire

Investigate linear static and normal modes analysis on a model and visualize displacement, factor of safety, percent of yield, tension and compression, von Mises stress, and major principal stress.

How-to
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