Struggling to apply AI? Join our hands-on Developer Connect on AI Fabric to learn how you can orchestrate all moving pieces of AI: deploy, consume, manage, and improve machine learning models. Let AI Fabric do the heavy lifting so you can reap the benefits from new cognitive workflows while focusing on your business.
About this event
Based on feedback from our last Developer Connect hands-on session, customers and partners want to learn more about UiPath AI Fabric.
Join our first Developer Connect on AI Fabric on Tuesday 15 September at 2.30pm NZST for 90 minutes. AI Fabric is one of the newer features of the UiPath Hyperautomation platform that brings Data Scientists and RPA teams together.
The session is instructor-led to train and deploy an ML model and is suitable for Developers. We will create a simple AI Fabric project and deploy it to UiPath Orchestrator and enable you to consume the ML skills we will create. Reviewing the problem of email classification that many companies face, we will train an ML model using AI Fabric and use it to classify the mail messages.
Below is the detailed agenda we will follow:
Create an AI Fabric project
Upload the dataset required to train the model
Write the python code that AI Fabric reads and trains the model – Knowledge of Python language is recommended
Train and test the model
Deploy the model on Orchestrator
Create a simple workflow using UiPath Studio to use the model
Please send me your name and email address before 5.00pm Monday 14 September so we can register you on the platform prior to the session commencing tomorrow. Email: email@example.com
Here is material:
This session is planned to be hands on, however we are structuring the session so that you can watch and listen. We will distribute all the material after the session so you can develop the solution in you own time. The reason being, everybody’s machine/laptop/desktop is different and hence you might get into issues while you code and not be able to keep up.
The following links will help you follow what is happening in the demonstration including concepts and terminology used.
Basic understanding of machine learning concepts and terminology is necessary