Regression Analysis Guide: A Comprehensive Guide for Data Analysts and Researchers

Daniel Garfield

Acheter 4,99 €
+ 4 points
Langue:
Ebook en anglais
ISBN:
9798224238583
Date de parution:
21-05-24
Editeur:
May Reads
Format:
Ebook
Format Détaillé:
EPUB
Protection digitale:
/

Description

In the age of artificial intelligence, data engineering plays a pivotal role in shaping the future. This comprehensive guide, "AI Data Engineering for Beginners," takes you on a journey through the core principles and practices that underpin the data-driven world of AI. Whether you're an aspiring data engineer, a curious enthusiast, or a student eager to understand the inner workings of AI, this book is your passport to the realm of data.

 

Key Features:

 

Demystifying AI: Dive into the world of artificial intelligence, unraveling its secrets and understanding how data engineering is the cornerstone of AI's magic. Data Dynamics: Discover the diverse landscape of data, including structured, unstructured, and semi-structured data, and learn how to harness its power. Building Blocks: Explore the tools and techniques for data collection and ingestion, transforming raw data into valuable insights. Storage Solutions: Navigate the realm of databases, data warehouses, and cloud storage, learning how to choose the right solution for your AI projects. Processing Power: Understand the significance of data processing, both in batch and real-time, and get hands-on with ETL processes and data pipelines. Integration and Cleaning: Master data integration, cleaning, and preprocessing, ensuring that your data is clean, consistent, and ready for machine learning. AI-Ready Data: Prepare your data for machine learning, including feature engineering, training data preparation, and deployment considerations. Real-world Insights: Gain inspiration from real case studies that showcase the challenges and solutions of AI data engineering. Future-proofing: Explore emerging trends in AI and data engineering, equipping you with knowledge about what the future holds. Tips for Success: Learn best practices, tackle common challenges, and discover potential career paths in AI data engineering.

 

This book bridges the gap between AI theory and practical implementation. With a wealth of real-world examples and hands-on guidance, you'll not only grasp the foundations of AI data engineering but also be ready to tackle your own AI projects. As the world becomes increasingly data-driven, your ability to shape, manage, and leverage data will be a sought-after skill, and "AI Data Engineering for Beginners" is your essential toolkit to step confidently into this exciting field. Whether you dream of revolutionizing industries or simply want to understand the tech shaping our world, this book is your starting point in mastering the data behind the AI revolution.