AI Integration and Deployment
Session with George Anadiotis (Founder, Principal Consultant, Linked Data Orchestration)
About this Session
From Algorithms to Applications: Streamlining AI Implementation for Business Value
Experience the practical side of AI implementation in this accessible session. Discover how modern frameworks and cloud services have democratized AI development. Navigate the landscape of leading AI frameworks and platforms as we demystify options like TensorFlow, PyTorch, and Scikit-learn. Explore how cloud giants AWS, Azure, and Google Cloud have streamlined AI service development.
Most importantly, discover how no-code and low-code solutions allow your organization to dabble in AI capabilities without specialized technical teams. Learn how AutoML tools can automatically optimize models for specific business problems, and understand how Model-to-Application frameworks bridge the gap between AI concepts and real-world business applications.
This strategic overview equips with the knowledge to make informed decisions about AI implementation pathways, helping you identify the most efficient routes to integrate AI solutions into your organization's workflow – regardless of your technical background.
- Outline
- Introduction
- Overview of popular AI frameworks:
- TensorFlow
- PyTorch
- Keras
- Scikit-learn
- Pandas
- Cloud-based AI services
- AWS
- Azure
- Google Cloud
- AutoML tools and platforms
- Model to Application frameworks
- Format
- This session is lecture-based.
- Level
- Intermediate
- Prerequisite Knowledge
- Data Fundamentals
- Learning Outcomes
- Knowledge of AI integration and deployment principles and lifecycle, AI frameworks, platforms, and services
