Data Augmentation with Python

Data augmentation is a vital step in improving the performance of machine learning models, and "Data Augmentation with Python" serves as your comprehensive guide. Through this book, you will learn how to augment datasets across image, text, audio, and tabular data formats, leveraging open-source libraries and Python-based tools. You'll gain practical exposure by working with real-world datasets and interactive notebook examples.

What this Book will help me do

• Master applying 20+ data augmentation techniques for images and text.
• Get hands-on experience with Python OOP code for data preprocessing.
• Learn to evaluate augmentation techniques for bias and parameter safety.
• Navigate advanced tools like BERT and Word2vec for text augmentation.
• Create rich visualizations of augmented datasets using Python libraries.

Author(s)

Duc Haba brings expertise in machine learning and data science, turning theory into practice with his accessible teaching. His hands-on approach emphasizes practical problem-solving, making his works valuable resources for learners. With decades of programming experience, Duc focuses on Python tools that matter.

Who is it for?

This book is perfect for data scientists and students looking to sharpen their AI and machine learning skills. It is beginner-friendly for those with Python programming and Jupyter Notebook familiarity, ensuring accessibility for a diverse technical audience. Whether you want to explore data augmentation or refine your analysis methods, this is for you.