Intelligent Automation using Machine Learning

What if your robots could predict which invoices will be paid late? See how to connect machine learning models to business processes and turn predictions into automated actions.

#1about 8 minutes

Understanding UiPath's robotic process automation platform

UiPath's core technology is an advanced robotic process automation (RPA) platform that uses computer vision and AI, not simple screen scraping.

#2about 9 minutes

Explaining the core concepts of machine learning

Machine learning uses algorithms to learn from historical data and create a mathematical model, like a function, to predict outcomes for new data.

#3about 2 minutes

Comparing traditional programming with machine learning

Unlike traditional programming where rules are explicitly coded, machine learning models automatically deduce complex rules and patterns directly from data.

#4about 4 minutes

Exploring types of machine learning and their applications

Supervised learning, which includes classification and regression, is the most common type of machine learning used for real-world applications like recommendation engines and predictive maintenance.

#5about 11 minutes

Navigating the machine learning project lifecycle

A successful machine learning project involves not just model training and evaluation, but also overcoming the significant challenges of data processing and productionizing the model for real-world use.

#6about 10 minutes

The strategic role of AI in digital transformation

Automation serves as the foundation for applied AI, enabling companies to digitize complex processes and accelerate their digital transformation initiatives.

#7about 7 minutes

An overview of AI features in the UiPath platform

The UiPath platform integrates AI across the entire automation lifecycle, from discovery with Process and Task Mining to building and managing models with AI Center.

#8about 6 minutes

Automating more with intelligent document processing

UiPath's Document Understanding uses AI to extract data from unstructured documents like invoices, with a human-in-the-loop process for validation and continuous model retraining.

#9about 3 minutes

Using AI to discover new automation opportunities

Process Mining analyzes system logs and Task Mining uses machine learning to analyze user actions, helping businesses scientifically identify and prioritize automation opportunities.

#10about 12 minutes

How to operationalize and expedite AI deployment

The UiPath platform simplifies deploying and managing AI models in production and expedites development by allowing easy combination of RPA, multiple ML models, and human input.

#11about 7 minutes

Introducing a use case for predicting late invoice payments

This use case addresses the business challenge of unpredictable cash flow by building a model to predict which customer invoices are likely to be paid late.

#12about 10 minutes

Building a model to predict late invoice payments

The prediction model is built using feature engineering on historical customer payment behavior and trained with XGBoost, achieving high accuracy in identifying late payments.

#13about 20 minutes

Demonstrating an AI-powered cash collection application

This live demo shows an end-to-end solution where robots collect data, an AI model predicts late payments, and a custom app enables the finance team to take immediate action.

#14about 12 minutes

Answering questions on use cases, ROI, and the platform

The team answers audience questions about identifying good machine learning use cases, calculating the return on investment for automation, and platform-specific features.