Chapter 1 Getting Started Data Analysis and Feature Engineering Chapter Goal Establish the premise of the problem we want to solve with machine learning. Analyze several data sets and process them. No of pages - 30 pages Sub - Topics 1. Premise 4. Data analysis 5. Feature engineering Chapter 2 Building a Machine Learning Model Chapter Goal Build a machine learning model on a data set several data sets that we processed the data for in chapter 4.No of pages - 40 pagesSub - Topics 1. Building the model 2. Training and testing the model 3. Validation and optimizing Chapter 3 What is MLOps Chapter Goal Introduce the reader to MLOps, various stages of automation in MLOps setups, automation with pipeline, and to CICD and CD Deployment. Pipelines for source repo to deployment, prediction services, performance monitoring, etc Continuous Integration source repo updated with new models, and Continuous Delivery new models deployed. No of pages - 40 pages Sub -Topics 1. What is MLOps 2. MLOps set