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GenAI Black Book: Python Edition (With All Codes & Concepts)

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Book Details
Language
English
Publishers
Independently published (24 May 2024)
Weight
0.36 KG
Publication Date
24/05/2024
Pages
271 pages
ISBN-13
9798326538444
Dimensions
15.24 x 1.57 x 22.86 cm
SKU
9798326538444
Author Name
Husn Ara (Author)
As a seasoned Data Scientist with over 11 years of experience in Data Science & Analytics, I bring a wealth of expertise to the table. With a Master's Degree in Computer Science and a Post Graduate Diploma in Data Science, I have honed my skills in Statistical Analysis and Data Visualization tools such as Tableau, Python (Matplotlib, Seaborn, Plotly Dash), Power BI, and Excel. My proficiency extends to GenAI, Statistics, Tensorflow, and various Machine Learning techniques and algorithms.Throughout my career, I have gained extensive experience in Image Processing, Computer Vision, and Deep Learning. I am well-versed in Regression, Classification, and Segmentation approaches, with a deep understanding of Python Language for Analytics and SQL Server. Moreover, I have demonstrated expertise in building Deep Neural Networks with Tensorflow, Keras & PyTorch.My portfolio of projects encompasses a diverse range of applications, including:Face Recognition model for online attendance systemObject detection in videoCustomer churn prediction modelFraud Detection ModelRecommender System ModelTime Series AnalysisCNC machine Autonomy ProjectSentiment AnalysisText Summarization using NLPGenerative AI projects, such as Image generation by prompt Text using ChatGPT ApIRoboticsIn the realm of Healthcare Diagnosis, I have developed robust models for:Lung Cancer Detection using both Image-Based and Symptoms-Based Models with high accuracy ratesLung Infection Detection with a multi-classification approach using VGG16 ModelAdditionally, I have contributed to Environment, Social, and Governance [ESG] projects involving data cleaning, preprocessing, visualization, and presentation creation for Stockholders.Furthermore, I have experience in Object Detection in Image and video using Yolo5.With a passion for leveraging data-driven insights to solve complex problems, I am committed to delivering innovative solutions that drive business growth and improve operational efficiency.I have successfully published technical Books on Data Science like:1) Zero to Machine Learning Hero2) Mastering GenAI Zero to Hero3) Tensorflow Mastery 2.04) All About Tensorflow5) Mastering Statistics for Data Science6) Become a Pro Data Scientist7) Mastering Robotics8) Mastering Prompt Engineering for GenAI9) Large Language Models for GenAIThanks for visiting my profile!Happy LearningHusn AraRead more about this authorRead less about this author
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Welcome to the "GenAI Black Book", an extensive guide crafted to unravel the fascinating world of Generative Artificial Intelligence (GenAI). As we stand on the cusp of a technological revolution, the ability of AI to create, innovate, and transform is becoming increasingly profound.

This book is designed to be your comprehensive companion on this journey, whether you are a novice taking your first steps into AI or an experienced practitioner looking to deepen your understanding. The Dawn of Generative AIGenerative AI represents a pivotal advancement in the field of artificial intelligence, enabling machines to generate text, images, music, and more, with creativity and coherence that often rival human outputs.

From generating realistic images to crafting compelling narratives, the applications of GenAI are as diverse as they are groundbreaking. This book aims to demystify these technologies, providing clear explanations, practical examples, and insightful discussions on their implications.

The book begins with an introduction to the fundamental concepts of generative AI, providing readers with a solid understanding of the underlying principles and methodologies. It covers various generative models, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers, elucidating their architectures, training procedures, and real-world use cases.

As readers progress through the chapters, they are introduced to advanced topics such as conditional generation, multimodal generation, unsupervised learning, LLM, LLAMA, Prompt Engineering and Retrieval-Augmented Generation (RAG) Framework, gaining hands-on experience through code examples and tutorials. The book also explores cutting-edge research and emerging trends in the field, offering insights into the future directions of generative AI.

With practical guidance and actionable insights, "GenAI Black Book " equips readers with the knowledge and skills needed to harness the power of generative AI for a wide range of applications, including art generation, content creation, natural language processing, and more. Whether you're a data scientist, AI enthusiast, or industry professional, this book serves as an invaluable resource for mastering the art and science of generative AI.

A Commitment to Responsible AIAs we explore the boundless potential of Generative AI, it is imperative to acknowledge and address the ethical and societal impacts of these technologies. The "GenAI Black Book" is committed to fostering a responsible and ethical approach to AI development and deployment, ensuring that these powerful tools are used to benefit society at large.

For the ReaderThis book is designed to be accessible to a wide audience. Each chapter builds upon the previous ones, making it suitable for both self-study and academic use.

Code examples are provided in Python, leveraging popular libraries such as Hugging Face's Transformers, to offer hands-on experience with implementing GenAI systems. We hope that the "GenAI Black Book" will inspire, educate, and empower you to explore the exciting possibilities of Generative AI.

Whether you aim to develop cutting-edge applications, contribute to research, or simply satisfy your curiosity, this book is your gateway to understanding and mastering Generative AI. Welcome to the future of creativity and innovation.

Welcome to the "GenAI Black Book". .

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