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