Table of Content
- Big Data Meet ML
- What is ML
- What is Big Data
- For Big Data Analysis we need Machine Learning
- For ML we need Big Data
- ML for data analysis in physics and other sciences
-
AI at Scale
- ML on Big Data
- Big Data -> Big Opportunities
- Big Data -> Big Challenges
- Survey of Machine Learning for Big DataProcessing
- Distributed ML Training
- Tools and Techniques for distributed Training
- Data parallelism / Model parallelism
- Compute resources for ML
- compute hardware for ML
- local vs cloud
- Why cloud
- When (not) cloud
- Cloud platform for ML
- Notebook server ad Full server solution
- Notebook: Colab, Gradient
- Full serer: Google Cloud, Azure
- A Close look at Azure Machine Learning
- Azure for student (with @unipg.it account)
- Azure ML Platform
- Azure ML Studio
- Azure ML SDK
- Training Workflow
- ML Pipeline / ML OPS
- Deploy