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Data Modeling Made Simple: A Practical Guide to Mastering Data Modeling for All Skill Levels by Lucas Plaisance
English | June 5, 2024 | ISBN: N/A | ASIN: B0D6CV5YNR | 76 pages | EPUB | 0.13 Mb
Simplify the complex world of data modeling with Data Modeling Made Simple: A Practical Guide to Mastering Data Modeling for All Skill Levels. This comprehensive guidebook, written in a clear and conversational style, empowers individuals of all backgrounds to understand, create, and utilize data models effectively.expand_more

Whether you're a business user, analyst, developer, or anyone who interacts with data, Data Modeling Made Simple provides you with the tools and knowledge you need. Master key concepts like data normalization, dimensional modeling, and the Data Model Scorecard. Learn to build different types of data models to suit various situations. Gain the confidence to interpret existing models and communicate data concepts with clarity.
This practical guide includes step-by-step explanations, real-world examples, and exercises to solidify your understanding. Unlock the power of data and gain a valuable skill with Data Modeling Made Simple.

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Data On Demand: High-Performance Computing with MOJO For Big Data Analytic by Travis M. Price
English | June 13, 2024 | ISBN: N/A | ASIN: B0D6NDGLWV | 145 pages | EPUB | 0.21 Mb
Discover the potential of MOJO, an innovative technology that enables the creation of high-performing machine learning models on large datasets. MOJO addresses big data's obstacles by allowing you to examine even the largest data streams and derive insightful information for quick decision-making.

Author of this book is Travis M. Price, a data science specialist with a wealth of knowledge in machine learning and big data analytics. He gives you a clear, succinct, and educational overview of MOJO so you can take use of its features and realize the full potential of your data.
Summary of the Book:Master MOJO: Gain a comprehensive understanding of MOJO's architecture, functionalities, and how it simplifies the process of building and deploying powerful machine learning models.Conquer Big Data Challenges: Discover how MOJO's distributed processing capabilities overcome the limitations of traditional machine learning tools when handling massive datasets.Stream Processing Power: Explore MOJO's ability to analyze data streams in real-time, enabling you to make faster and more informed decisions based on up-to-the-minute insights.Seamless Integration: Learn how MOJO integrates with popular big data tools and frameworks, creating a robust data science workflow for efficient data analysis.Security Made Simple: Implement robust security practices to protect your data and ensure the safe and reliable deployment of your MOJO models.Natural Language Processing (NLP) Applications: Delve into how MOJO can be used to analyze text data, opening doors to new possibilities for data analysis.What's Inside:Step-by-step guidance on building and deploying MOJO modelsPractical examples and use cases to illustrate MOJO's capabilitiesClear explanations of complex conceptsCode examples to enhance understanding for developers of all experience levelsBest practices for data security and model deploymentAbout the Reader:
Data scientists, analysts, developers, and business professionals who wish to use MOJO to glean insightful information from large data sets should read this book. This book gives you the knowledge and resources you need to be successful, whether you're new to MOJO or want to brush up on the subject.
Put an end to your struggles with limited model capabilities and poor processing times. With the help of this book, you may quickly become proficient in MOJO and discover the full potential of big data analytics.
Turn your data into insights that you can use right now! Become a revolution in data science by obtaining a copy of "Data on Demand: High-Performance Computing with MOJO for Big Data Analytics".

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DATA SCIENCE: An Emerging Trend in Engineering, Science & Technology by MRUNALINI MOON, ANKITA SHENDE, MONIKA WALDE
English | June 16, 2024 | ISBN: N/A | ASIN: B0D2D84R26 | 432 pages | EPUB | 36 Mb
Data science is a deep study of the massive amount of data, which involves extracting meaningful insights from raw, structured, and unstructured data that is processed using the scientific method, different technologies, and algorithms. It is a multidisciplinary field that uses tools and techniques to manipulate the data so that you can find something new and meaningful.

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DATA SCIENCE AND PYTHON NUMPY FOR BEGINNERS: UNLOCKING THE SECRETS OF DATA SCIENCE: STEP-BY-STEP INSTRUCTIONS FOR ASPIRING DATA SCIENTISTS - 2 BOOKS IN 1 by JP PARKER
English | June 3, 2024 | ISBN: N/A | ASIN: B0CYV9B6PY | 392 pages | EPUB | 0.26 Mb
"Data Science Demystified: A Beginner's Guide to Mastering Data Analysis and Machine Learning for Career Success - Unlocking the Secrets of Data Science: Step-by-Step Instructions for Aspiring Data Scientists".

In this comprehensive guide, we demystify the complex field of data science, making it accessible to beginners and aspiring data scientists alike. Whether you're a college student exploring career options or a professional looking to transition into the exciting world of data science, this book provides everything you need to get started on your journey.
**Unlock the Secrets of Data Science**
Discover the fundamentals of data analysis and machine learning in easy-to-understand language. From understanding data structures and algorithms to mastering statistical techniques and predictive modeling, this book covers it all. Step-by-step instructions and practical examples guide you through each concept, ensuring you develop a strong foundation in data science.
**Master Data Analysis and Machine Learning**
Gain hands-on experience with data analysis and machine learning techniques using popular tools and programming languages such as Python, R, and SQL. Learn how to collect, clean, and analyze data effectively, and build powerful machine learning models to extract insights and make data-driven decisions.
**Why Choose "Data Science Demystified"?**
- Comprehensive coverage of data science fundamentals
- Easy-to-follow explanations and practical examples
- Hands-on experience with popular tools and programming languages
- Insights from industry experts and real-world case studies
- Practical tips for career development and job search strategies
Python NumPy for Beginners: Unleash the Power of Data Science with Easy-to-Follow Tutorials
In today's data-driven world, NumPy is the backbone of data science, machine learning, and scientific research. This beginner-friendly ebook is your key to unlocking the immense capabilities of NumPy, even if you have little to no prior experience in Python or data science.
**What You'll Learn:**
- **Foundation of NumPy:** Start with the basics as you build a strong foundation in NumPy. Discover how to install NumPy, create arrays, and perform basic operations with easy-to-follow tutorials.
- **Data Manipulation:** Dive into the world of data manipulation and learn how NumPy simplifies tasks like cleaning, transforming, and reshaping data for analysis.
- **Statistical Analysis:** Explore NumPy's powerful statistical functions for data analysis, from calculating means and medians to finding correlations and percentiles.
- **Visualization:** Learn how to visualize your data effectively using MatDescriptionlib and gain insights from your datasets with clear, informative Descriptions and charts.
- **Machine Learning Integration:** Understand how NumPy seamlessly integrates with machine learning libraries like scikit-learn, making it an invaluable tool for building predictive models.
- **Advanced Techniques:** Elevate your skills by delving into advanced NumPy topics such as broadcasting, memory management, and GPU acceleration.
- **Real-World Projects:** Apply your knowledge to practical projects, including data analysis, visualization, and machine learning, to solve real-world challenges.
**Why This Ebook?**
- **Beginner-Friendly:** Designed with beginners in mind, this ebook offers a gentle and approachable introduction to NumPy, making it suitable for students, self-learners, and aspiring data scientists.

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Data Science for Beginners: Unlocking the Power of Data for teens, beginners and all those keen-agers by Nitin Bhatia
English | June 16, 2024 | ISBN: N/A | ASIN: B0D1NW37S1 | 183 pages | EPUB | 4.23 Mb
Welcome to "Data Science for Beginners," your gateway to the fascinating world of data science! This book is designed for curious young minds and enthusiastic beginners who want to explore the power of data in a fun and engaging way. Dive into an exciting journey where learning meets adventure, and discover how data shapes the world around us in incredible ways.What Will You Learn?

This book covers a wide range of topics to give you a comprehensive understanding of data science:
Introduction to Data Science: Start your journey with an overview of what data science is and why it's important. Learn about the history and evolution of data science, and how it impacts various fields such as healthcare, finance, and marketing.
Machine Learning Basics: Discover the exciting world of machine learning, where computers learn from data and make predictions. Understand different types of machine learning, including supervised and unsupervised learning. See how algorithms can recognize patterns and make decisions, powering technologies like recommendation systems and voice assistants.
Big Data and Data Engineering: Delve into the realm of big data and understand how massive amounts of information are processed and analyzed. Learn about the technologies and frameworks that make big data analysis possible, such as Hadoop and Spark. Explore the role of data engineers in managing and optimizing data workflows.
Ethical Considerations in Data Science: Data science is not just about numbers and algorithms; it's also about making responsible choices. Explore the ethical aspects of data collection and analysis, including data privacy, bias in machine learning models, and the importance of fairness and transparency. Learn how to use data in a way that is ethical and respectful of people's rights.
Fun and Engaging Learning
Learning should be an adventure, and this book ensures that it is! Packed with interactive activities, quizzes, and engaging stories, this book makes data science come alive. Meet curious characters who guide you through data adventures, solve puzzles, and test your knowledge with quizzes designed to reinforce what you've learned.
Who Is This Book For?Kids: Young learners aged 10 and up who are curious about data, technology, and how things work.Beginners: Anyone new to data science who wants to learn the basics in a simple and engaging way.Parents and Educators: Those looking for a fun and educational resource to introduce children to data science.About the Author
Nitin is a passionate educator and data science enthusiast dedicated to making complex concepts accessible to young minds. With years of experience in teaching and a knack for storytelling, Nitin brings data science to life in a way that's both informative and entertaining.
Join the Data Science Revolution
Data science is not just a subject; it's a superpower. By understanding data, you can make informed decisions, solve problems, and even create new technologies. This book is your gateway to becoming a data superhero. Start your journey today and unlock the power of data with fun and easy lessons designed just for you.
Build Your Data Science Toolkit
As you progress through this book, you'll build a toolkit of skills and knowledge that you can use in everyday life. Learn how to collect, analyze, and visualize data. Understand the basics of programming languages like Python, which is widely used in data science. Develop critical thinking and problem-solving skills that are valuable in any field.

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Data, Strategy, Culture & Power: Win with Data-Centric AI by making human nature work for you by Nicole Radziwill, Morgan Benton
English | May 15, 2024 | ISBN: N/A | ASIN: B0D4BGHVJ6 | 210 pages | EPUB | 0.85 Mb
Companies will spend more than $200B on AI hardware, software, systems & services each year from 2025 through 2030, but 75%+ of these initiatives are projected to fail. The remaining 25% will only realize a return on investment (ROI) of 6% or less... far short of the promise of AI.

What is everyone missing?
The best AI comes from the best data, and the best data comes from the best people. But even the best people are impacted by subconscious bias, past trauma, interpersonal relationships, and power dynamics... no one is immune to human nature. This book was written to help you navigate the pitfalls of perception, build a foundation for trust, and elevate organizational performance. Make your data and AI initiatives succeed where others fail.
"Data, Strategy, Culture & Power" is a must-read for anyone who works with (or uses) data, analytics, and AI in today's complex organizations. This book challenges the notion that data always leads to objective insights, exposing the ways in which power differentials and biases short circuit rational behavior - and what leaders can do about it.
Data can not be decoupled from power. By embracing the imperfections inherent in data and human nature, this book shows how data-centric AI can be both a blessing and a curse - and how you can make the best of it.
Part I: Navigating the Pitfalls of Perception
Chapter 1: Beware of the Limits of Truth
Chapter 2: Beware of Your Own Brain
Chapter 3: Beware of Other People
Chapter 4: Beware of Collective Delusion
Part II: Building a Foundation for Trust
Chapter 5: Data Integrity is Process Integrity
Chapter 6: Knowing What "Good" Means
Chapter 7: Evidence, Context & Action
Part III: Elevating Organizational Performance
Chapter 8: Anticipate Fragility
Chapter 9: Infuse Data with Power
Chapter 10: Create Beliefs that Inspire
Chapter 11: Raise the Bar

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Database Design Using Entity-Relationship Diagrams (Foundations of Database Design) by Sikha Saha Bagui, Richard Walsh Earp
English | September 1, 2022 | ISBN: 103201718X | 388 pages | MOBI | 7.13 Mb
Essential to database design, entity-relationship (ER) diagrams are known for their usefulness in data modeling and mapping out clear database designs. They are also well-known for being difficult to master. With Database Design Using Entity-Relationship Diagrams, Third Edition, database designers, developers, and students preparing to enter the field can quickly learn the ins and outs of data modeling through ER diagramming.

Building on the success of the bestselling first and second editions, this accessible text includes a new chapter on the relational model and functional dependencies. It also includes expanded chapters on Enhanced Entity-Relationship (EER) diagrams and reverse mapping. It uses cutting-edge case studies and examples to help readers master database development basics and defines ER and EER diagramming in terms of requirements (end user requests) and specifications (designer feedback to those requests), facilitating agile database development. This bookDescribes a step-by-step approach for producing an ER diagram and developing a relational database from itContains exercises, examples, case studies, bibliographies, and summaries in each chapterDetails the rules for mapping ER diagrams to relational databasesExplains how to reverse engineer a relational database back to an entity-relationship modelIncludes grammar for the ER diagrams that can be presented back to the user, facilitating agile database developmentThe updated exercises and chapter summaries provide the real-world understanding needed to develop ER and EER diagrams, map them to relational databases, and test the resulting relational database. Complete with a wealth of additional exercises and examples throughout, this edition should be a basic component of any database course. Its comprehensive nature and easy-to-navigate structure make it a resource that students and professionals will turn to throughout their careers.

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Databricks Fundamentals: Everything You Need to Know to Get Started with Databricks by Fabiano Rodrigues da Silva
English | June 6, 2024 | ISBN: N/A | ASIN: B0D6HZ9JVW | 113 pages | EPUB | 5.16 Mb
This e-book takes you on a complete journey into the world of data analysis with Databricks, one of the leading platforms for big data processing and machine learning. From grasping the basics to implementing advanced strategies, each chapter covers essential aspects to master the use of Databricks in complex data environments.

Throughout this e-book, you'll be guided through a series of concepts and practices, from understanding the importance of data management to generating valuable insights through exploratory analysis and creating informative reports. Additionally, you'll learn techniques for automation and task scheduling to optimize workflow and maximize operational efficiency.
With a practical, results-oriented approach, this e-book is designed for professionals at all levels of experience in data analysis, offering a comprehensive understanding of Databricks and its applications in solving real-world challenges.
By the end of this e-book, you'll be ready to tackle the complex challenges of the data analysis world, armed with the knowledge and skills needed to excel in your professional journey.

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Dealing with Dilemmas: Applied Game Theory for Medical Executive Committees to Deal with Difficult Peer Issues by Paul Murphree
English | January 29, 2024 | ISBN: N/A | ASIN: B0CTKJC773 | 80 pages | EPUB | 4.04 Mb
Dealing with Dilemmas" unravels the intricacies of decision-making and strategic thinking within Medical Executive Committees (MECs), presenting an invaluable resource for those committed to elevating their leadership acumen in the ever-evolving landscape of medicine.

This groundbreaking book transcends traditional procedural and legal concepts, delving into the challenging terrain that physician leaders often navigate. By spotlighting the principles of the strategic "game" inherent in these situations, the book provides a fresh perspective on the complexities surrounding MEC decisions. A game theory primer lays the groundwork, offering a foundational understanding of the strategic elements that shape decision-making.
Armed with this essential knowledge, readers gain insights into the causes of inaction, shedding light on the underlying dynamics that can impede progress. "Dealing with Dilemmas" goes beyond the surface, addressing the common defense strategies employed by physicians. In doing so, it equips MECs with the discernment needed to sift through these approaches, maintaining focus on a strategic path that prevents the recurrence of these challenging issues. "Dealing with Dilemmas" is your essential companion on the journey to effective and strategic leadership in the complex world of healthcare governance.

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Debugging Machine Learning Models with Python: Develop high-performance, low-bias, and explainable machine learning and deep learning models by Ali Madani
English | September 15, 2023 | ISBN: 1800208588 | 344 pages | EPUB | 13 Mb
Master reproducible ML and DL models with Python and PyTorch to achieve high performance, explainability, and real-world success

Key Features:
Learn how to improve performance of your models and eliminate model biasesStrategically design your machine learning systems to minimize chances of failure in productionDiscover advanced techniques to solve real-world challenges
Book Description:
Debugging Machine Learning Models with Python is a comprehensive guide that navigates you through the entire spectrum of mastering machine learning, from foundational concepts to advanced techniques. It goes beyond the basics to arm you with the expertise essential for building reliable, high-performance models for industrial applications. Whether you're a data scientist, analyst, machine learning engineer, or Python developer, this book will empower you to design modular systems for data preparation, accurately train and test models, and seamlessly integrate them into larger technologies.
By bridging the gap between theory and practice, you'll learn how to evaluate model performance, identify and address issues, and harness recent advancements in deep learning and generative modeling using PyTorch and scikit-learn. Your journey to developing high quality models in practice will also encompass causal and human-in-the-loop modeling and machine learning explainability. With hands-on examples and clear explanations, you'll develop the skills to deliver impactful solutions across domains such as healthcare, finance, and e-commerce.
What You Will Learn:
Enhance data quality and eliminate data flawsEffectively assess and improve the performance of your modelsDevelop and optimize deep learning models with PyTorchMitigate biases to ensure fairnessUnderstand explainability techniques to improve model qualitiesUse test-driven modeling for data processing and modeling improvementExplore techniques to bring reliable models to productionDiscover the benefits of causal and human-in-the-loop modeling
Who this book is for:
This book is for data scientists, analysts, machine learning engineers, Python developers, and students looking to build reliable, high-performance, and explainable machine learning models for production across diverse industrial applications. Fundamental Python skills are all you need to dive into the concepts and practical examples covered. Whether you're new to machine learning or an experienced practitioner, this book offers a breadth of knowledge and practical insights to elevate your modeling skills.

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Decentralized Computing: The Evolution of Power and Possibility by Saimon Carrie
English | June 27, 2024 | ISBN: N/A | ASIN: B0D8BK963Z | 115 pages | EPUB | 1.20 Mb
"Decentralized Computing: The Evolution of Power and Possibility" explores the transformative impact of blockchain and decentralized technologies on our world today and in the future. From revolutionizing finance and governance to empowering individuals and communities, decentralized computing represents a paradigm shift in how we interact, transact, and govern.

In this insightful exploration, we delve into the foundational principles of decentralization, tracing its evolution from the creation of Bitcoin to the emergence of smart contracts and decentralized applications (dApps) on platforms like Ethereum. We uncover how these technologies have democratized access to financial services through decentralized finance (DeFi), enabling peer-to-peer transactions, lending, and investing without intermediaries.
Moreover, the book examines how decentralized networks are reshaping governance models, with innovations like Decentralized Autonomous Organizations (DAOs) enabling transparent decision-making and community-driven initiatives. We explore the potential of blockchain to enhance data privacy and digital autonomy through self-sovereign identity solutions and decentralized storage systems, empowering individuals to control their personal information securely.
"Decentralized Computing" also addresses the challenges and opportunities inherent in this technological revolution. It navigates regulatory landscapes, security considerations, and scalability issues while advocating for ethical and responsible innovation. The book underscores the potential of decentralized computing to drive sustainable development, promote environmental stewardship, and foster inclusive economic growth.
Through compelling case studies, expert insights, and visionary perspectives, "Decentralized Computing: The Evolution of Power and Possibility" invites readers to understand and embrace the transformative potential of decentralized technologies. It is an essential read for policymakers, entrepreneurs, technologists, and anyone curious about the future of digital innovation and its profound implications for society.

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Deception Decoded: Mastering the Art of Reading People: Spotting Lies, Understanding Character, and Building Trust in Relationships by Anna W Price
English | June 30, 2024 | ISBN: N/A | ASIN: B0D8JFCZCC | 164 pages | EPUB | 0.67 Mb
In a world where deception lurks around every corner and relationships are complex webs of hidden truths and motivations, understanding the people around us is more crucial than ever. This book delves into the art of seeing through deception, identifying true character, and navigating social interactions with confidence and insight.

Starting with an in-depth exploration of the notorious Pig Butchering Scheme, readers will learn how to safeguard themselves from falling prey to sophisticated scams. The book then transitions into practical advice on how to identify lies and spot scammers, especially on social media.
Understanding human behavior is key to discerning truth from deception. This book offers detailed guidance on observing subtle cues in behavior, from dining etiquette to the impact individuals have on their surroundings. It provides practical techniques for mastering the art of reading people, enabling readers to uncover the true character behind facades.
For those seeking to understand the complexities of romantic relationships, the book provides invaluable insights into identifying reliable partners and avoiding scumbags. Case studies and character traits are dissected to help readers make informed decisions about who to trust and who to avoid.
The book also explores the nuances of women's behavior, helping readers distinguish between high emotional intelligence and manipulative traits. Through real-life examples, it highlights the characteristics of both admirable and undesirable partners.
Beyond interpersonal relationships, the book covers the concept of aura and its impact on personal interactions. It provides tips on how to develop a strong presence and recognize it in others.

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Decisive Leadership: Transforming Complex Challenges into Competitive Edge by Avva Thach
English | May 30, 2024 | ISBN: N/A | ASIN: B0D5RDK9KS | 244 pages | EPUB | 5.61 Mb
Are you tired of second-guessing your decisions, feeling overwhelmed by complex challenges, and struggling to lead with confidence? Imagine a future where you approach every business decision with clarity, conviction, and strategic foresight - where you effortlessly navigate uncertainty and emerge victorious, time and time again.

1. Decision-Making Strategies: Uncover effective decision-making strategies tailored for executive leaders grappling with complexity.
2. Competitive Analysis: Learn how to conduct thorough competitive analysis and identify opportunities for strategic differentiation.
3. Execution Excellence: Discover tactics for executing strategic initiatives with precision and agility to stay ahead in dynamic markets.
This book empowers executive leaders to transform complex business challenges into opportunities for competitive advantage. By providing practical decision-making strategies, guidance on competitive analysis, and insights into execution excellence, readers will gain the confidence and capability to drive strategic clarity and success in just 90 days.

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Decoding AI: A Guide to Explainable Artificial Intelligence for Professionals by Rosey Press
English | July 17, 2024 | ISBN: N/A | ASIN: B0D9PK28NY | 53 pages | EPUB | 0.25 Mb
Explainable AI (XAI) is a concept that focuses on making the decision-making process of artificial intelligence models transparent and understandable to humans. As AI systems become more complex and integrated into various industries, the need for explainability has become increasingly important, especially in sensitive fields like healthcare and finance. With XAI, professionals can better understand how AI systems arrive at their decisions, leading to increased trust and accountability.

One of the main challenges in developing explainable AI models is finding the right balance between performance and interpretability. While highly complex AI models may achieve high accuracy, they can be difficult to interpret and explain. Creating standards for explainability and addressing ethical concerns surrounding AI decision-making are also key challenges in the field of XAI. However, by overcoming these challenges, professionals can harness the power of AI while ensuring transparency and accountability.
In healthcare, XAI is being used to improve transparency and trust in medical AI systems, ultimately leading to better patient outcomes. By explaining how AI models make diagnostic and treatment decisions, healthcare professionals can better understand and trust the recommendations provided by these systems. In finance, XAI is being implemented in financial institutions to increase accountability and reduce bias in decision-making processes. By making AI-driven decisions transparent and understandable, financial professionals can ensure fair and ethical practices in the industry.
In addition to healthcare and finance, XAI is being applied in a wide range of industries, including legal, marketing, autonomous vehicles, education, cybersecurity, environmental science, human resources, and social media. In each of these fields, explainable AI is enhancing transparency, improving decision-making processes, and increasing trust between AI systems and human professionals. By incorporating XAI into various industries, professionals can leverage the power of AI while ensuring ethical and responsible practices.
Overall, explainable AI plays a crucial role in bridging the gap between AI systems and human professionals. By making AI decision-making processes transparent and understandable, XAI empowers professionals to trust and utilize AI systems in a wide range of industries, ultimately leading to better outcomes for both businesses and society as a whole.

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Deep Learning at Scale: At the Intersection of Hardware, Software, and Data by Suneeta Mall
English | July 23, 2024 | ISBN: 1098145283 | 448 pages | MOBI | 8.27 Mb
Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required.

This book illustrates complex concepts of full stack deep learning and reinforces them through hands-on exercises to arm you with tools and techniques to scale your project. A scaling effort is only beneficial when it's effective and efficient. To that end, this guide explains the intricate concepts and techniques that will help you scale effectively and efficiently.
You'll gain a thorough understanding of:How data flows through the deep-learning network and the role the computation graphs play in building your modelHow accelerated computing speeds up your training and how best you can utilize the resources at your disposalHow to train your model using distributed training paradigms, i.e., data, model, and pipeline parallelismHow to leverage PyTorch ecosystems in conjunction with NVIDIA libraries and Triton to scale your model trainingDebugging, monitoring, and investigating the undesirable bottlenecks that slow down your model trainingHow to expedite the training lifecycle and streamline your feedback loop to iterate model developmentA set of data tricks and techniques and how to apply them to scale your training modelHow to select the right tools and techniques for your deep-learning projectOptions for managing the compute infrastructure when running at scale

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