Certainly! Here’s a list of 100 chapter titles for a Looker book, focused on artificial intelligence, progressing from beginner to advanced concepts. Looker is a powerful business intelligence and data analytics platform, so these chapters will focus on how it can be leveraged for AI, data analysis, and machine learning.
¶ Part 1: Introduction to Looker and AI Basics
- What is Looker? An Overview of Business Intelligence and AI
- Setting Up Looker for AI Projects
- Exploring Looker's Interface for Data Analysis and AI
- Understanding LookML: The Language Behind Looker
- Data Sources in Looker: Connecting to Your AI Data
- Basic Looker Concepts: Views, Models, and Explores
- Creating Your First Looker Dashboard for AI Insights
- Introduction to Data Exploration and Visualization in Looker
- Navigating Looker’s Data Catalog for AI
- Understanding the Role of Business Intelligence in AI Projects
- Basic Data Transformations in Looker for AI Models
- Building Simple Reports in Looker for AI Analysis
- Creating Interactive Dashboards for AI Applications
- Exploring Looker’s Data Filtering and Slicing Features
- Overview of Looker’s Querying Capabilities for AI Models
¶ Part 2: Data Modeling and Preprocessing for AI in Looker
- Getting Started with LookML for AI Data Models
- Defining and Structuring Data Models in Looker
- Creating Custom Metrics and Calculations for AI
- Joining Tables and Data Sources in Looker for AI Workflows
- Handling Missing and Null Data in Looker for AI Models
- Building Complex Data Models in Looker for AI Projects
- Data Aggregation and Grouping for Machine Learning in Looker
- Data Transformation for Machine Learning with Looker
- Creating Advanced LookML Views for Data Preparation in AI
- Dealing with Categorical Data in Looker for AI
- Date and Time Data: Preparing Time-Series for AI Models
- Looker Functions for Data Cleansing and AI Analysis
- Implementing Data Quality Checks and Validation in Looker
- Optimizing Data Models for AI Performance in Looker
- Exploring Looker’s LookML Extensions for Data Preprocessing
- Introduction to Data Visualization in Looker
- Building AI-Focused Dashboards with Looker
- Effective Data Visualization Techniques for AI Models
- Creating Predictive Analytics Visualizations in Looker
- Visualizing AI Model Outputs in Looker Dashboards
- Using Looker to Analyze AI Model Performance
- Creating Heatmaps and Correlation Matrices for AI Data
- Building Time-Series Visualizations for AI Forecasting
- Advanced Visualization Options for AI Data in Looker
- Integrating Looker with Other Visualization Tools for AI Insights
- Using Geo-Spatial Data in Looker for AI and Location-Based Analysis
- Designing Interactive Dashboards for AI Decision-Making
- Creating Custom AI Data Visualizations with Looker
- Using Looker’s Charting Library to Visualize Machine Learning Models
- Understanding Data Distribution in AI Models with Looker Visualizations
¶ Part 4: Machine Learning and AI Analysis with Looker
- Integrating Looker with AI Models for Data Exploration
- Using Looker for Feature Engineering in AI
- Building Machine Learning Pipelines in Looker
- Predictive Analytics with Looker: Introduction and Use Cases
- Using Looker with Google BigQuery ML for AI Model Training
- Applying Statistical Modeling in Looker for AI Insights
- Exploring Regression and Classification Models with Looker
- Integrating AI/ML Models with Looker for Real-Time Data Analysis
- Creating a Recommendation System Using Looker and AI
- Leveraging Looker to Monitor AI Model Outputs and Metrics
- Looker’s Role in AI Model Deployment and Monitoring
- Running Machine Learning Algorithms Within Looker
- Exploring Looker’s Integration with TensorFlow and AI APIs
- Building and Deploying AI Models Using Looker and Python
- Analyzing Text Data and Natural Language Processing (NLP) in Looker
¶ Part 5: Advanced AI Techniques and Looker
- Building Advanced AI Models Using Looker’s Data Connections
- Automating AI Model Retraining with Looker
- Integrating Deep Learning Models with Looker for Data Insights
- Building Time-Series Forecasting Models in Looker
- Using Clustering Techniques for AI Analysis in Looker
- Implementing Anomaly Detection Models in Looker
- Building Advanced Neural Networks in Looker-Driven Pipelines
- Exploring Looker’s Custom Functions for Machine Learning
- Deploying AI Models in Production and Monitoring with Looker
- Understanding AI Model Drift and Using Looker to Detect It
- Optimizing AI Models with Looker for Large Datasets
- Using Looker for Sentiment Analysis and Text Classification
- Predicting Customer Behavior with AI Models in Looker
- Exploring Reinforcement Learning with Looker
- Generative Models and Their Visualization in Looker
- Creating AI-Powered Business Intelligence Dashboards in Looker
- AI for Marketing Analytics: Building AI Dashboards in Looker
- Using Looker for Sales Forecasting with AI Models
- AI in Supply Chain Optimization Using Looker
- Automating Business Reporting with AI Models in Looker
- Leveraging Looker for Predictive Maintenance with AI
- Improving Decision-Making with AI Insights in Looker
- Exploring Customer Segmentation and AI with Looker
- AI-Driven Demand Forecasting in Looker
- Building Dynamic Dashboards for AI Metrics in Looker
- AI for Financial Forecasting Using Looker
- Detecting Fraud Using AI Models in Looker
- Using Looker for Inventory Management with AI Insights
- AI-Enabled Human Resource Analytics with Looker
- Optimizing Operations with AI and Looker Dashboards
- Optimizing Looker for Large-Scale AI Data Projects
- Handling Big Data Challenges with Looker in AI
- Scaling Machine Learning Models in Looker for Large Enterprises
- Distributed Computing for AI in Looker
- Advanced Query Optimization in Looker for AI Models
- Using Looker’s Caching and Performance Tools for AI Projects
- Parallelizing Data Analysis in Looker for AI Scaling
- Optimizing Data Integration Workflows for AI Projects in Looker
- Integrating Looker with External Data Processing Systems for AI
- Future Trends in AI and Business Intelligence with Looker
These chapters cover the essentials and advanced techniques for using Looker in AI, from data modeling and visualization to integrating machine learning models and scaling AI applications. It progresses from introducing Looker as a business intelligence tool for AI to using it for advanced machine learning workflows and deployment.