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Paperback. Condition: new. Paperback. The book begins with fundamental GenAI concepts, including GPT-4 and Gemini, and mastering prompt engineering for optimal GenAI interaction. Instead of starting with technical details like algorithms and syntax, it introduces coding through interactive, practical Python Jupyter Notebooks and Google Colab projects. Readers will learn Python code with a calculator application, explore fundamental sorting algorithms, and manipulate data using Pandas. The book then explores advanced ML through CNN image classification with Fast.ai, and deploying AI models as web applications using Hugging Face and Gradio. It also addresses critical ethical considerations in AI, focusing on fairness and bias, and provides career guidance for modern programmers. Moreover, this book takes a fresh approach to learning by prioritizing exploration and creativity, much like the way Gen Z engage with games, apps, and hands-on activities. Write and debug Python code through hands-on projects. Learn GenAI setup, and effective prompt engineering. Step-by-step Python projects using Jupyter Notebooks and GenAI. Deploy AI models as interactive web applications using Hugging Face and Gradio frameworks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - DESCRIPTIONGenAI and Python are changing how we use technology, making it essential to understand both to stay innovative and work efficiently. GenAI significantly impacts learning Python by generating personalized code snippets, accelerating the learning process. This book bridges the gap between traditional education and the practical challenges students encounter today. It combines hands-on learning with modern GenAI tools like GPT-4 and Copilot.The book begins with fundamental GenAI concepts, including GPT-4 and Gemini, and mastering prompt engineering for optimal GenAI interaction. Instead of starting with technical details like algorithms and syntax, it introduces coding through interactive, practical Python Jupyter Not Elektronisches Buch and Google Colab projects. Readers will learn Python code with a calculator application, explore fundamental sorting algorithms, and manipulate data using Pandas. The book then explores advanced ML through CNN image classification with Fast.ai, and deploying AI models as web applications using Hugging Face and Gradio. It also addresses critical ethical considerations in AI, focusing on fairness and bias, and provides career guidance for modern programmers. Moreover, this book takes a fresh approach to learning by prioritizing exploration and creativity, much like the way Gen Z engage with games, apps, and hands-on activities.By the end of this book, you will be equipped with the practical skills and ethical understanding to confidently apply Python and GenAI in diverse projects, helping you navigate the evolving landscape of AI-driven development.WHAT YOU WILL LEARN¿ Write and debug Python code through hands-on projects.¿ Learn GenAI setup, and effective prompt engineering.¿ Step-by-step Python projects using Jupyter Not Elektronisches Buch and GenAI.¿ Deploy AI models as interactive web applications using Hugging Face and Gradio frameworks.¿ Leverage GenAI tools like GPT-4 and Copilot.¿ Understand AI bias and use it responsibly for positive impact.WHO THIS BOOK IS FORThis book is for professionals interested in learning Python and using GenAI tools like GPT-4 in practical applications. It is for aspiring programmers, students, and data analysts seeking practical Python and GenAI skills.
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 Elektronisches BuchKey Features:Explore 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 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 Not Elektronisches Buch, 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.What You Will Learn:Write 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 for:This 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 Not Elektronisches Buch are essential to understanding the topics covered in this book.
Taschenbuch. Condition: Neu. Data Augmentation with Python | Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data | Duc Haba | Taschenbuch | Englisch | 2023 | Packt Publishing | EAN 9781803246451 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.