AWS Innovate 2019 AI/ML Edition
Table of Contents
AWS Innovate 2019 - AI/ML Edition
:ID: AWS-INNOVATE-2019-AI
Event Details
- Date: March 5, 2019 (Americas), October 17, 2019 (EMEA)
- Time: 9:00 AM - 1:30 PM PT / 12:00 PM - 4:30 PM ET
- Location: Virtual (Online Conference)
- Cost: Free
- Level: 100-200 (Beginner to Intermediate)
Target Audience
- Developers building intelligent applications
- Data Scientists working with ML models
- IT Professionals exploring AI services
- Data Engineers managing ML pipelines
Key Topics
Smart Applications (No ML Experience Required)
- Add intelligence to existing applications with managed AI services
- Vision, speech, and language capabilities
- Chatbot development
- Forecasting and personalization
Building, Training, and Deploying Models
- Lowering costs and improving ML workflow
- Data labeling best practices
- Model building and training techniques
- Production deployment and hosting
Notable Speakers
Julien Simon
- Global Evangelist for AI & ML at AWS
- Focus on helping developers bring ideas to life
- Frequent conference speaker and blogger
Sunil Mallya
- Lead, Machine Learning Solutions Lab
- Specialization in Deep Learning and Reinforcement Learning
- Former co-founder of Neon Labs (neuroscience and ML image analysis)
Denis Batalov
- 13-year Amazon veteran with PhD in Machine Learning
- Worked on Search Inside the Book, Amazon Mobile, Kindle Direct Publishing
- Worldwide Tech Leader for ML & AI
AWS Services Covered
- Amazon SageMaker - Build, train, and deploy ML models
- Amazon Rekognition - Image and video analysis
- Amazon Comprehend - Natural language processing
- Amazon Transcribe - Speech to text
- Amazon Polly - Text to speech
- Amazon Lex - Conversational interfaces (chatbots)
- Amazon Forecast - Time series forecasting
- Amazon Personalize - Recommendation systems
Resources
- AWS Innovate Registration: https://aws.amazon.com/events/aws-innovate/
- AWS ML/AI Services: https://aws.amazon.com/machine-learning/
- SageMaker Documentation: https://docs.aws.amazon.com/sagemaker/
Key Themes
- Accessibility - Making ML accessible without deep expertise
- Managed Services - Pre-built AI capabilities via APIs
- End-to-End Workflow - From data preparation to production deployment
- Real-World Applications - Practical use cases across industries