From the eBook - [First edition].
Part 1: Starting with GCP and Python
Chapter 1: Comprehending Google Cloud Services
Understanding the GCP global infrastructure
Creating a free-tier GCP account
Provisioning our first computer in Google Cloud
Provisioning our first storage in Google Cloud
Managing resources using GCP Cloud Shell
GCP organization structure
The GCP resource hierarchy
GCP Identity and Access Management
Load balancers and managed instance groups
Containers and Google Kubernetes Engine
GCP storage and database service spectrum
GCP big data and analytics services
GCP artificial intelligence services
Chapter 2: Mastering Python Programming
Basic Python variables and operations
Basic Python data structure
Python conditions and loops
Opening and closing files in Python
Python data libraries and packages
Part 2: Introducing Machine Learning
Chapter 3: Preparing for ML Development
Starting from business requirements
ML model inputs and outputs
Measuring ML solutions and data readiness
ML model performance measurement
Data sampling and balancing
Numerical value transformation
Categorical value transformation
Chapter 4: Developing and Deploying ML Models
Decision tree and random forest
More classification metrics
Overfitting and underfitting
Testing and deploying the model
Practicing model development with scikit-learn
Chapter 5: Understanding Neural Networks and Deep Learning
