Data Preparation for AI and Analytics

In the world of ML and AI, data preparation is the key component!

Data Preparation for AI and Analytics is a practical guide to one of the most critical yet underappreciated aspects of the data science and AI pipeline – the preparing of data to be fed into your machine learning and AI models. This book provides end-to-end coverage from initial data exploration through quality assessment, transformation, enrichment, and final preparation for both analytics and ML applications.

“Data is food for AI” – those are the words of Andrew Ng founder of DeepLearning.AI and prominent expert in the field. Making sure that your models have good nourishing “food” is the most critical and often time-intensive part of data science. This book helps you meet that need by balancing theoretical foundations with implementation details, making the book valuable for both newcomers and experienced practitioners.

In Data Preparation for AI and Analytics you’ll:

• Understand the importance of data quality and why to pursue it
• Perform exploratory analysis to understand new datasets
• Clean, transform, and organize your data to drive decision making
• Deal with missing data and inconsistencies in your data
• Merge data from different sources into a unified stream
• Build explainability into your models right from the start
• Apply generative AI techniques to automate repetitive tasks
• Use AI to boost data quality and simplify workflows
• Apply the right data preparation technique for the right outcome

The quality and integrity of your data determine the accuracy, reliability, and usefulness of your AI models. Investing substantial effort in data preparation isn't just beneficial—it's essential. Your investment into data preparation as described in this book leads to more accurate predictions and actionable insights as well as to more confident business decisions.

Data Preparation for AI and Analytics is for data engineers who build data pipelines in support of AI models, machine learning models, and business analytics. It presents data preparation methods with clear language and concrete examples. You’ll explore tried-and-true approaches along with emerging generative AI techniques. You’ll especially appreciate the insights into automation and data governance.