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WeAreDevelopers LIVE • May 26, 2021

Intelligent Automation using Machine Learning

Boris Krumrey , Andreas Palfi , Radu Pruna

Are brittle selectors breaking your automated workflows? Discover how machine learning models replace hardcoded logic to deduce rules, handle exceptions, and drive definitive business actions.

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#1 about 8 min

Introduction to UiPath and robotic process automation

The platform evolved from basic screen scraping algorithms to intelligent interface understanding using complex computer vision models.

#2 about 10 min

How machine learning approximates reality through mathematical functions

Algorithms estimate the best mathematical function from historical data sets to describe relationships between inputs and outputs.

#3 about 2 min

Deducing rules from data instead of manual programming

Machine learning models automatically learn decision rules from data characteristics instead of requiring explicitly coded logic statements.

#4 about 5 min

Overview of supervised, unsupervised, and reinforcement learning

The major categories of machine learning solve discrete business use cases through structured classification and regression approaches.

#5 about 5 min

Core stages of training and managing machine learning models

Real data science efforts heavily involve data processing pipelines and engineering tasks rather than simply tuning state-of-the-art algorithms.

#6 about 7 min

Moving machine learning models into production automation flows

Integrating prediction engines into user applications enables operational teams to act upon predictions and continuously retrain models.

#7 about 10 min

Using automation as the foundation for digital transformation

Companies scale digitization efforts by deploying automation flows that generate the metadata required for subsequent artificial intelligence initiatives.

#8 about 11 min

Building an end-to-end platform for automation and AI

Extending rule-based robotics with integrated cognitive capabilities enables robust task optimization across complex enterprise software environments.

#9 about 4 min

Processing unstructured data through intelligent document understanding

Combining robotic process automation with continuously trained models allows accurate data extraction from customized forms and handwritten papers.

#10 about 3 min

Uncovering automation opportunities via process and task mining

Machine learning tools analyze system logs and desktop interactions to visualize poorly standardized manual tasks that need optimization.

#11 about 11 min

Operationalizing custom and pre-built machine learning models securely

Connecting various narrow intelligence tools via application programming interfaces expedites secure model deployment for non-technical software developers.

#12 about 7 min

Break and automated assistant feature recorded demonstrations

Recorded system demonstrations show a locally running automation assistant handling resume screening and new employee onboarding flows.

#13 about 4 min

Selecting context-appropriate performance metrics for prediction models

Applying highly imbalanced training sets requires robust accuracy metrics like F1 scores rather than naive overall capability measurements.

#14 about 8 min

Predicting overdue invoices to improve accounts receivable collection

Classifying historical customer payment behaviors helps financial teams flag late payments before their assigned scheduling due dates.

#15 about 10 min

Transforming tabular metrics into meaningful business value dashboards

Structuring complex gradient boosted output into monetary confusion matrices enables operational stakeholders to prioritize financial payment collection efforts.

#16 about 13 min

Building a comprehensive accounts receivable cash collection application

A backend virtual machine triggers system scripts that pull client invoice data to predict delinquencies via deployed machine-learning backends.

#17 about 9 min

Executing independent automation workflows outside browser environments

Connected endpoint robots execute localized backend processes rather than utilizing client-side web browser compute processing constraints.

#18 about 5 min

Identifying appropriate business use cases for deploying artificial intelligence

Ideal automation targets involve high-volume, variable workflows where traditional deterministic rule-based logics become practically impossible to maintain accurately.

#19 about 7 min

Calculating return on investment and comparative software advantages

Dedicated evaluation portals synthesize operational effort requirements against monetary benefits while supporting both localized and cloud-deployed orchestration software methods.

Matching moments

6:31 min

Identifying valid use cases for process automation

Johannes Ostner Johannes Ostner · Europe 2026 Virtual

4:01 min

Transitioning artificial intelligence into operational business environments

Stefan Donsa Stefan Donsa +1 · LIVE

2:05 min

Enhancing case matching with integrated machine learning tools

Clemens Schwaiger · LIVE

4:37 min

Introduction to the speakers and process automation transformation journey

Kevin Kaiser Kevin Kaiser +1 · World Congress 2025

1:12 min

Building intelligent applications and enhancing developer productivity experiences

Alexander Wallner Alexander Wallner +3 · World Congress 2024

4:15 min

Introduction to artificial intelligence driven development

Natalie Pistunovich · LIVE

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