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Unlock the Power of UiPath AI Center API

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UiPath AI Center API is a powerful tool that allows you to unlock the full potential of UiPath's AI center capabilities. It enables you to integrate AI models and machine learning algorithms into your UiPath automation workflows, providing you with enhanced automation capabilities and the ability to make intelligent decisions. Please join us at this session, where you can learn more. Today's topics will cover: đź“Ś What is UiPath AI Center đź“Ś Create a sample AI center project đź“Ś Steps to generate an AI Center API and utilize it in a UiPath Project đź“Ś Benefits and ways of utilization

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UiPath Dallas Chapter
Unlock the Power of UiPath AI Center API
#UiPathDallasChapter
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About UiPath Denver Chapter!
We are an online and offline environment where RPA
developers, professionals, and enthusiasts:
- meet each other and share experiences in the RPA
industry
- learn together about the challenges they encounter
- build projects and components together and expand
upon automation ideas
Platforms:
- UiPath Community Page
- Slack Channel
Solution Architect
Ashling Partners
Naveen
Chatlapalli
Organizers/Team
UiPath AI ambassador Americas
UiPath MVP 2023
UiPath Denver chapter lead
Sr. Machine Learning Consultant
Ashling Partners
Sharon
Palawandram Diana Gray
Community Leader
Community Marketing Manager
UiPath
Introduction
AI Center API
Q&A
Meeting Agenda
AI Center
What is UiPath AI Center
UiPath AI Center is a service provided by UiPath that allows users to
deploy, manage, and continuously improve machine learning models and
incorporate them into Robotic Process Automation (RPA) workflows
. It enables users to leverage the power of artificial intelligence (AI) and
machine learning (ML) in their automation processes.
5
Data Preparation
Model Development
Model Training and
Evaluation
Phases Involved in leveraging AI Center
Model Deployment
Integration with RPA
Workflows
Continuous Improvement

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Unlock the Power of UiPath AI Center API

  • 1. UiPath Dallas Chapter Unlock the Power of UiPath AI Center API #UiPathDallasChapter
  • 2. 2 About UiPath Denver Chapter! We are an online and offline environment where RPA developers, professionals, and enthusiasts: - meet each other and share experiences in the RPA industry - learn together about the challenges they encounter - build projects and components together and expand upon automation ideas Platforms: - UiPath Community Page - Slack Channel
  • 3. Solution Architect Ashling Partners Naveen Chatlapalli Organizers/Team UiPath AI ambassador Americas UiPath MVP 2023 UiPath Denver chapter lead Sr. Machine Learning Consultant Ashling Partners Sharon Palawandram Diana Gray Community Leader Community Marketing Manager UiPath
  • 5. What is UiPath AI Center UiPath AI Center is a service provided by UiPath that allows users to deploy, manage, and continuously improve machine learning models and incorporate them into Robotic Process Automation (RPA) workflows . It enables users to leverage the power of artificial intelligence (AI) and machine learning (ML) in their automation processes. 5
  • 6. Data Preparation Model Development Model Training and Evaluation Phases Involved in leveraging AI Center Model Deployment Integration with RPA Workflows Continuous Improvement
  • 17. Demo
  • 18. Education Learn RPA Skills - Free Community Software - Academy - Certification - Academic Alliance Support Solve problems - Forum - Documentation - Community Blog - Use Cases Repository - Job Board Network Grow your career - Meetups & DevCon - Mentorship - Hackathons - MVP Program - Automation Champions An ecosystem enabling developer success
  • 19. Vibrant ecosystem of more than 1.5 million professionals and citizen developers learning, getting support, and succeeding together in their automation careers. • Start with the free Community Edition to get trained and certified • Then upgrade to the Enterprise version of the product Academy • Get crowdsourced support and share product feedback on UiPath Forum • Check the product documentation • Join the Insider Preview for early testing Forum Community Events • Access the latest articles and video tutorial content created by community members and UiPath engineers in our Community Blog • Contribute as an author. UiPath Community MVPs • Get recognized as a Most Valuable Professional (MVP), Automation Champion or one of the Forum Leaders, based on the contribution to others’ growth Join the UiPath Community • Connect with like-minded people and share best practices with the UiPath Community • Solve challenges in engaging hackathon competitions • Join meetups and conferences Blog and Tutorials Automation Cloud • Learn the skills of the future on UiPath Academy or through our Academic Alliance • Earn globally recognized credentials with UiPath Certifications

Editor's Notes

  1. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  2. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  3. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  4. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  5. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  6. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  7. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  8. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]
  9. ChatGPT is a variant of the GPT (Generative Pre-training Transformer) language model that was developed specifically for generating human-like text in a conversational context. It is designed to generate natural language responses when given input from a user — making it potentially useful in a variety of business applications where human-like conversation with customers or clients is desirable. Proximal Policy Optimization, or PPO, is a policy gradient method for reinforcement learning. The motivation was to have an algorithm with the data efficiency and reliable performance of TRPO, while using only first-order optimization. The particular semi-supervised approach OpenAI employed to make a large scale generative system—and was first to do with a transformer model—involved two stages: an unsupervised generative "pre-training" stage to set initial parameters using a language modeling objective, and a supervised discriminative "fine-tuning" stage to adapt these parameters to a target task.[13]