Description: Data Augmentation with Python by Duc Haba The book helps you grasp images, text, audio, and tabular augmentation methods using real-world datasets from the Kaggle website. Throughout the chapters, youll discover augmentation concepts and techniques, a review of available open source augmentation libraries, and a reinforcement learning section through Python Notebook coding exercises. FORMAT Paperback CONDITION Brand New Publisher Description Boost your AI and generative AI accuracy using real-world datasets with over 150 functional object-oriented methods and open source librariesPurchase of the print or Kindle book includes a free PDF eBookKey FeaturesExplore beautiful, customized charts and infographics in full colorWork with fully functional OO code using open source libraries in the Python Notebook for each chapterUnleash the potential of real-world datasets with practical data augmentation techniquesBook DescriptionData 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. Youll 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, youll 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.What you will learnWrite OOP Python code for image, text, audio, and tabular dataAccess over 150,000 real-world datasets from the Kaggle websiteAnalyze biases and safe parameters for each augmentation methodVisualize data using standard and exotic plots in colorDiscover 32 advanced open source augmentation librariesExplore machine learning models, such as BERT and TransformerMeet Pluto, an imaginary digital coding companionExtend your learning with fun facts and fun challengesWho this book is forThis book is for data scientists and students interested in the AI discipline. Advanced AI or deep learning skills are not required; however, knowledge of Python programming and familiarity with Jupyter Notebooks are essential to understanding the topics covered in this book. Author Biography Mr. Duc Haba is a lifelong technologist and researcher specializing in Deep Learning and Generative AI. He has been a programmer, Enterprise Mobility Solution Architect, AI Solution Architect, Principal, VP, CTO, and CEO. The companies range from startups and IPOs to enterprise companies.Ducs career started with Xerox Palo Alto Research Center (PARC), researching expert systems (ruled-based) for Xerox copier diagnostics. After PARC, he joined Oracle, following Viant Consulting as a founding member. He jumped headfirst into the entrepreneurial culture in Silicon Valley. There were slightly more failures than successes, but the highlights are working with Oracle, Viant, and RRKidz. Currently, he is happy working at YML as the AI Solution Architect. Table of Contents Table of ContentsData Augmentation Made EasyBiases in Data AugmentationImage Augmentation for Classification Image Augmentation for SegmentationText AugmentationText Augmentation with Machine LearningAudio Data AugmentationAudio Data Augmentation with SpectrogramTabular Data Augmentation Details ISBN1803246456 Author Duc Haba Publisher Packt Publishing Limited Year 2023 ISBN-13 9781803246451 Format Paperback Imprint Packt Publishing Limited Place of Publication Birmingham Country of Publication United Kingdom AU Release Date 2023-04-21 NZ Release Date 2023-04-21 Pages 394 Publication Date 2023-04-28 Subtitle Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data DEWEY 006.31 Audience Professional & Vocational UK Release Date 2023-04-28 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:142025052;
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