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Key Benefits

Explore beautiful, customized charts and infographics in full color

Work with fully functional OO code using open source libraries in the Python Notebook for each chapter

Unleash the potential of real-world datasets with practical data augmentation techniques

What You Will Learn

Write OOP Python code for image, text, audio, and tabular data

Access over 150,000 real-world datasets from the Kaggle website

Analyze biases and safe parameters for each augmentation method

Visualize data using standard and exotic plots in color

Discover 32 advanced open source augmentation libraries

Explore machine learning models, such as BERT and Transformer

Meet Pluto, an imaginary digital coding companion

Extend your learning with fun facts and fun challenges

Book Description

Data is paramount in AI projects, especially for deep learning and generative AI, as forecasting accuracy relies on input datasets being robust. Acquiring additional data through traditional methods can be challenging, expensive, and impractical, and data augmentation offers an economical option to extend the dataset. The book teaches you over 20 geometric, photometric, and random erasing augmentation methods using seven real-world datasets for image classification and segmentation. You’ll also review eight image augmentation open source libraries, write object-oriented programming (OOP) wrapper functions in Python Notebooks, view color image augmentation effects, analyze safe levels and biases, as well as explore fun facts and take on fun challenges. As you advance, you’ll discover over 20 character and word techniques for text augmentation using two real-world datasets and excerpts from four classic books. The chapter on advanced text augmentation uses machine learning to extend the text dataset, such as Transformer, Word2vec, BERT, GPT-2, and others. While chapters on audio and tabular data have real-world data, open source libraries, amazing custom plots, and Python Notebook, along with fun facts and challenges. By the end of this book, you will be proficient in image, text, audio, and tabular data augmentation techniques.

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Amazon verified reviews

Dr. Matthias Nagel Aug 11, 2023

Amazon Verified review

Ady Ngom Jun 14, 2023

The author's passion for teaching really shines through this piece. A definitive must read if you want to start navigating the world of possibilities with AI and need a solid compass to guide you through.

crawdaddie Jul 05, 2023

"Boosting AI Accuracy with Real-World Datasets" is a helpful and practical guide for people who want to use Python and improve their AI models using data augmentation techniques. The book has lots of useful information, easy-to-understand explanations, and practical examples that allow readers to learn and become skilled in enhancing images, text, audio, and tabular data. This book is a valuable resource because of its practical approach.Data augmentation is a required technique for improving AI accuracy, and Duc Haba does an excellent job of explaining various augmentation methods using real-world datasets. Whether it's image, text, audio, or tabular data, readers will find detailed explanations, code samples, and insights into the biases and safe parameters for each augmentation method.The book covers a wide range of topics, providing over 150 functional object-oriented methods and open-source libraries to help readers achieve optimal results. This book is accessible to aspiring data scientists and those interested in the AI discipline, even without prior AI or deep learning skills.

Poker Nanny Jun 07, 2023

This book effectively introduces readers to the topic of Data Augmentation. While the subject itself is vast and cannot be thoroughly explored in a single book, the author takes a practical approach by presenting various recipes that demonstrate different techniques for augmenting data across a variety of categories. Considering its scope, this book serves its purpose well in acquainting readers with Data Augmentation. Personally, I found the chapter on Biases in Data Augmentation to be the highlight of the book.

Om S Jun 06, 2023

"Data Augmentation with Python" is an essential guide for data scientists and students seeking to improve AI accuracy using real-world datasets. With over 150 functional methods and open source libraries, the book covers image, text, audio, and tabular data augmentation. The author emphasizes the importance of robust datasets in AI projects and presents practical techniques for extending data economically. Through Python code examples and Jupyter Notebooks, readers gain hands-on experience with various augmentation methods. The inclusion of colorful charts and custom plots enhances understanding, while fun facts and challenges add an engaging touch. Suitable for beginners and experienced practitioners, this book equips readers with the skills to enhance AI accuracy through effective data augmentation.

Data Augmentation with Python

Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data

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Data Augmentation with Python

Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data

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