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Lower Extremity Nerve Entrapments: Clinical Diagnosis and Treatment
English | 2025 | ISBN: 303190057X | 206 Pages | PDF EPUB (True) | 171 MB
This book offers a comprehensive and in-depth exploration of lower limb nerve entrapments, integrating anatomical, diagnostic, and therapeutic perspectives. The journey begins with an examination of the epidemiology, shedding light on its prevalence and distribution. Building on this foundation, readers delve into the general aspects of neuropathies, gaining insights into the various manifestations and underlying mechanisms of nerve disorders affecting the lower limbs.
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LS Central For Beginners by AGI Publishing
English | November 14, 2024 | ISBN: N/A | ASIN: B0DN5119PK | 560 pages | EPUB | 0.41 Mb
Unlock the full potential of your retail business with LS Central For Beginners, the definitive guide to mastering one of the most powerful ERP and POS systems in the market today. Whether you're a retailer looking to streamline operations, enhance customer experiences, or drive profitability, this comprehensive guide will walk you through every feature and function of LS Central, the industry-leading solution owned by Goldman Sachs.
Written for beginners and non-technical personnel, this book covers everything you need to know to effectively implement and utilize LS Central's robust capabilities, from setting up your retail store to managing inventory, optimizing customer relationships, and leveraging powerful analytics.
Inside This Book, You'll Discover:Step-by-step instructions to get started with LS Central and navigate its user-friendly interface.How to manage products, inventory, and pricing to ensure seamless operations.Best practices for handling customer relationships and creating loyalty programs that drive repeat business.Advanced reporting and analytics tools to gain actionable insights into your business performance.How to leverage CRM features to personalize customer experiences and boost satisfaction.Practical tips on optimizing inventory levels, reducing costs, and enhancing efficiency.Packed with real-world examples, practical tips, and clear explanations, LS Central For Beginners is designed to demystify the complexities of ERP and POS systems, empowering you to drive growth and achieve operational excellence in your retail business.
Whether you're a store manager, business owner, or IT professional, this guide will equip you with the skills and knowledge to unlock the full potential of LS Central. Start your journey towards mastering your retail operations and taking your business to the next level!
Perfect for:Retailers, store managers, and business owners looking to streamline operations.IT professionals seeking to implement LS Central in their organizations.Anyone new to LS Central who wants to gain a strong foundation in using this powerful ERP and POS system.Transform your retail business today with LS Central For Beginners - your comprehensive guide to operational success!
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Mach 5 and Beyond
English | 2024 | ISBN: B0DKNPWL47 | Pages: 720 | EPUB (True) | 4.43 MB
This book provides a comprehensive exploration of hypersonic technology, focusing on its growing significance in modern warfare. It is structured into five parts, each addressing a different aspect of hypersonic weapons.
Part I lays the foundation, explaining the definition, types, and characteristics of hypersonic weapons, such as glide vehicles and cruise missiles. It covers the physics of hypersonic flight, the challenges posed by extreme speeds, and the materials needed to withstand such conditions. A detailed analysis of propulsion systems like scramjets and ramjets highlights future innovations in this field.
In Part II, the book delves into the development and testing of hypersonic weapons. It explores their evolution, from Cold War-era experiments to modern programs led by the U.S., Russia, and China. Testing facilities and challenges associated with high-speed flight, such as wind tunnels and simulation tools, are discussed in depth.
Part III addresses the military and strategic implications of hypersonic weapons. It emphasizes their offensive capabilities, the difficulty of defending against them, and their role in global power dynamics. The global arms race is examined, with a focus on how hypersonic weapons fit into national defence strategies, and the delicate balance between conventional and nuclear systems is considered.
Part IV outlines the technical challenges and countermeasures to hypersonic weapons, including detection and interception difficulties. International collaboration on missile defence and the ethical and legal concerns surrounding these weapons are also explored.
Finally, Part V looks to the future, discussing emerging technologies, the potential for space-based hypersonic platforms, and the changing nature of warfare in a hypersonic age. The book concludes with insights into the future challenges and opportunities presented by hypersonic weapons in global security.
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Machine Learning: Algorithms, Theory and Practice - A Comprehensive Hands-On Guide with Python
English | 2025 | ISBN: B0F3NTXL32 | Pages: 584 | Epub | 29.84 MB
Machine Learning: Algorithms, Theory and Practice - A Comprehensive Hands-On Guide with Python
Unlock the power of machine learning with a guide designed to take you from foundational concepts to cutting-edge applications. Machine Learning: Algorithms, Theory, and Practice is your all-in-one companion for mastering the theory and hands-on techniques behind modern ML systems-crafted for students, developers, educators, and professionals alike.
This comprehensive guide is structured for progressive learning. You'll start with the essentials of AI and Python programming, then advance through data preprocessing, statistical modeling, and classical machine learning algorithms. From there, you'll dive into deep learning, natural language processing (NLP), reinforcement learning, and generative AI-each topic reinforced with real-world coding exercises and clear explanations.
Inside, you'll find:
Foundational theory and intuitive explanations of key ML concepts, including supervised and unsupervised learning, regression, classification, clustering, and model evaluation.
Practical tutorials using Python and essential libraries such as NumPy, pandas, scikit-learn, and matDescriptionlib.
Practical tutorials that lead you through the process of building, training, and testing machine learning models
Advanced coverage of neural networks, CNNs, RNNs, BERT, transformer models, and diffusion-based generative AI.
Bonus content, including around 300 glossary terms, frequently asked questions, and hands-on guidance for using Jupyter Notebooks effectively.
Whether you're aiming for AI certifications, transitioning into a machine learning role, or applying ML techniques to real-world challenges, this book provides both the conceptual clarity and practical skills to help you thrive in the evolving world of machine learning.
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Machine Learning and Artificial Intelligence For Beginners : Data Processing, Model Evaluation Hyper parameter Tuning and Deployment Strategies (From Coding ... Success: The Ultimate Programming Series)
English | 2025 | ASIN: B0DTVSR14C | 187 pages | Epub | 432.84 KB
Unlock the Future: Revolutionize Your World with Machine Learning and Artificial Intelligence* Are you curious about the technologies transforming our world? Do you want to gain a competitive edge in the job market or boost your business? Look no further! This comprehensive guide is designed specifically for beginners, providing a clear and concise introduction to the exciting realms of Machine Learning and Artificial Intelligence. *Discover the Power of AI and ML* Through this book, you'll gain a solid understanding of the fundamental concepts, techniques, and tools used in Machine Learning and Artificial Intelligence. You'll learn how to: - Build intelligent systems that can learn and adapt - Make data-driven decisions with confidence - Automate tasks and processes with ease - Create innovative solutions to real-world problems *What Sets This Book Apart* This book offers a unique blend of theoretical foundations and practical applications, making it easy to grasp complex concepts. You'll find: - Real-world examples and case studies illustrating the successful implementation of AI and ML - Step-by-step tutorials and exercises to help you practice and reinforce your learning - Insights from industry experts and researchers, providing a glimpse into the future of AI and ML *Don't Miss Out on the AI Revolution* The demand for AI and ML expertise is skyrocketing, and this book provides the perfect starting point for your journey. Whether you're a student, professional, or entrepreneur, you'll gain the skills and knowledge to: - Stay ahead of the curve in a rapidly changing job market - Drive business growth and innovation with AI-powered solutions - Unlock new opportunities and possibilities in the exciting world of AI and ML *Start Your Learning Journey Today!* Dive into the world of Machine Learning and Artificial Intelligence, and discover the incredible potential of these transformative technologies. Get your copy of this beginner-friendly guide now and begin building the skills and expertise you need to succeed in the AI-driven future!"
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Machine Learning For Beginners Guide Algorithms: Supervised & Unsupervsied Learning. Decision Tree & Random Forest Introduction
English | 2017 | ISBN: B074YJYWDY | Pages: 268 | EPUB (True) | 497.23 KB
Machines can LEARN ?!?!
Machine learning occurs primarily through the use of " algorithms" and other elaborate procedures
Whether you're a novice, intermediate or expert this book will teach you all the ins, outs and everything you need to know about machine learning
Note: Bonus chapters included inside!
Instead of spending hundreds or even thousands of dollars on courses/materials why not read this book instead? Its a worthwhile read and the most valuable investment you can make for yourself
Other books easily retail for
$50-$100+
and have far less quality content. This book is by far superior and exceeds any other book available for beginners.
What You'll Learn
Supervised Learning
Unsupervised Learning
Reinforced Learning
Algorithms
Decision Tree
Random Forest
Neural Networks
Python
Deep Learning
And much, much more!
This is the most comprehensive and easy to read step by step guide in machine learning that exists.
Learn from one of the most reliable programmers alive and expert in the field
You do not want to miss out on this incredible offer!
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Machine Learning for Beginners: No Math Required
English | 2025 | ISBN: 9798231135158 | Pages: | EPUB (True) | 597.44 KB
"Machine Learning for Beginners: No Math Required"
Are you fascinated by artificial intelligence but intimidated by complex equations? Do terms like "neural networks" and "deep learning" leave you confused?
Machine Learning for Beginners
is your no-fear guide to understanding AI-using plain language and real-world examples instead of complicated math.
In this accessible guide, you'll discover:
Core Concepts Made Simple
- Learn supervised/unsupervised learning, neural networks, and deep learning without a single equation
How AI Powers Our World
- Explore applications in healthcare, finance, marketing, and self-driving cars
Hands-On Skills
- Get started with Python, popular tools, and build your first ML project
Ethical AI Fundamentals
- Understand bias, fairness, and how to create responsible algorithms
Future of Technology
- Discover where AI is heading and how you can be part of it
Who is this book for?
✔ Absolute beginners curious about machine learning
✔ Professionals who want AI literacy for their career
✔ Entrepreneurs exploring tech opportunities
✔ Anyone who's been put off by technical textbooks before
No calculus. No linear algebra. Just clear, practical knowledge.
Your AI education starts here-download the cheat sheets included with purchase!
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Machine Learning for Disease Detection, Prediction, and Diagnosis: Challenges and Opportunities
English | 2025 | ISBN: 9789819642410 | 389 pages | True PDF,EPUB | 16 MB
The book "Machine Learning for Disease Detection, Prediction, and Diagnosis" can be a comprehensive guide to the novel concepts, techniques, and frameworks essential for improving the viability of existing machine-learning practices. It provides an in-depth analysis of how these new technologies are helpful to detect, predict and diagnose diseases more accurately. The book covers various topics such as image classification algorithms, supervised learning methods like support vector machines (SVM), deep neural networks (DNNs), convolutional neural networks (CNNs), etc. unsupervised approaches such as clustering algorithms as well as reinforcement learning strategies.
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Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques
English | 2023 | ISBN: B0C4B5H7GB | Pages: 547 | EPUB (True) | 8.93 MB
As machine learning practitioners, we often encounter imbalanced datasets in which one class has considerably fewer instances than the other. Many machine learning algorithms assume an equilibrium between majority and minority classes, leading to suboptimal performance on imbalanced data. This comprehensive guide helps you address this class imbalance to significantly improve model performance.
Machine Learning for Imbalanced Data begins by introducing you to the challenges posed by imbalanced datasets and the importance of addressing these issues. It then guides you through techniques that enhance the performance of classical machine learning models when using imbalanced data, including various sampling and cost-sensitive learning methods.
As you progress, you'll delve into similar and more advanced techniques for deep learning models, employing PyTorch as the primary framework. Throughout the book, hands-on examples will provide working and reproducible code that'll demonstrate the practical implementation of each technique.
By the end of this book, you'll be adept at identifying and addressing class imbalances and confidently applying various techniques, including sampling, cost-sensitive techniques, and threshold adjustment, while using traditional machine learning or deep learning models.
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Machine Learning for Quants: Algorithms for Predicting Market Movements
English | 2024 | ISBN: B0DGLTZNHZ | Pages: 454 | EPUB (True) | 1.77 MB
In the era of big data and digital transformation, finance is no longer confined to traditional methods and human intuition. *Machine Learning for Quants: Algorithms for Predicting Market Movements* delves into the fascinating intersection of finance and advanced data science, illuminating the path for quantitative analysts to leverage machine learning techniques in the quest for market supremacy. This comprehensive guide bridges the gap between complex algorithms and practical financial applications, offering readers a meticulous yet accessible exploration of the tools needed to predict stock prices, design robust trading strategies, and manage risks effectively.
Throughout its well-structured chapters, the book covers fundamental aspects of quantitative finance, data preprocessing, and the intricacies of supervised and unsupervised learning. Detailed case studies exemplify the transformative power of these techniques in real-world financial scenarios. Whether you're a beginner taking your first steps in finance or a seasoned professional looking to enhance your skill set, *Machine Learning for Quants* is your gateway to mastering the sophisticated strategies that are reshaping the financial industry. Dive in and embark on a journey that promises to revolutionize your approach to financial markets.
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Machine Learning Fundamentals: Concepts, Models, and Applications
English | 2025 | ISBN: 1637427484 | 264 pages | PDF | 5.52 MB
Machine Learning Fundamentals provides a comprehensive overview of data science, emphasizing machine learning (ML). This book covers ML fundamentals, processes, and applications, that are used as industry standards. Both supervised and unsupervised learning ML models are discussed.
Topics include data collection and feature engineering techniques as well as regression, classification, neural networks (deep learning), and clustering. Motivated by the success of ML in various fields, this book is designed for a wide audience coming from various disciplines such as engineering, IT, or business and is suitable for those getting started with ML for the first time.
This text can also serve as the main or supplementary text in any introductory data science course from any discipline, offering real-world applications and tools in all areas.
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Machine Learning Hero: Master Data Science with Python Essentials: Machine Learning with Python Hands-On Guide from Beginner to Expert by Cuantum Technologies
English | October 6, 2024 | ISBN: 889587353X | 984 pages | PDF | 6.71 Mb
This Book grants Free Access to our e-learning Platform, which includes:
Free Repository Code with all code blocks used in this book Access to Free Chapters of all our library of programming published books Free premium customer support Much more...Become a Machine Learning Hero and Master Data Science with Python
In a world driven by data, mastering machine learning is your key to unlocking new opportunities and solving complex problems. Whether you're a beginner or a professional looking to sharpen your skills, Machine Learning Hero: Master Data Science with Python Essentials is your guide to becoming proficient in machine learning and data science.
This book provides a step-by-step journey into data science using Python, giving you the tools and knowledge to solve real-world problems confidently.
What You Will Learn
Master Python for Data Science
Learn how to use Python and essential data science libraries such as NumPy, Pandas, MatDescriptionlib, Seaborn, and Scikit-learn to manipulate, visualize, and analyze data efficiently.
Prepare Data for Machine Learning
Explore techniques for cleaning, transforming, and preparing raw data, including handling missing values, feature scaling, and encoding categorical variables to ensure your models are accurate and reliable.
Build Classical Machine Learning Models
Understand and implement popular machine learning algorithms such as:Linear and Polynomial Regression for predicting continuous outcomes.Classification algorithms like Support Vector Machines (SVMs), K-Nearest Neighbors (KNN), and Decision Trees to categorize data.K-Means Clustering for discovering patterns in data without labels.
Master Feature Engineering
Learn the art of feature engineering, transforming raw data into features that improve model performance. Feature engineering is key to building effective machine learning models that produce meaningful results.Hands-On Projects to Solidify Learning
Put theory into practice with hands-on projects designed to help you apply machine learning techniques in real-world scenarios
redict Car Prices: Use linear regression to estimate car prices based on factors like mileage, year, and make.Customer Segmentation: Use K-Means clustering to group customers by behavior, helping businesses understand their clients better.Classification Models: Apply classification algorithms to predict survival on the Titanic, using precision, recall, and AUC-ROC metrics to evaluate performance.These projects reinforce the key concepts and ensure you gain the practical experience needed to tackle real-world data challenges.Who Is This Book For?Aspiring data scientists wanting to build a solid foundation in machine learning.Python developers looking to expand their skillset into data science.Professionals seeking to use machine learning to solve problems and make data-driven decisions.Whether you're just getting started or aiming to improve your machine learning skills, this book provides everything you need to become a machine learning hero.
Start Your Journey Now
With Machine Learning Hero: Master Data Science with Python Essentials, you'll be equipped to handle real-world data challenges and unlock the potential of machine learning across any industry.
Are you ready to transform your data into actionable insights and become a machine learning hero?
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Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs
English | 2024 | ISBN: B0DGS8C4K9 | Pages: 351 | EPUB (True) | 345.47 KB
Unlock the full potential of machine learning with "Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs." This essential guide meticulously navigates through the intricate world of cloud-based ML APIs across the leading platforms-Google Cloud, AWS, and Azure. Whether you're a software developer, data scientist, IT professional, or business strategist, this book equips you with the knowledge to make informed decisions about implementing and managing these powerful tools in your projects.
Dive deep into a comprehensive analysis and comparison of text processing, image recognition, speech recognition, and custom model building services offered by these giants. Understand the ins and outs of setting up, configuring, and optimizing these APIs for performance and scalability. Explore chapters dedicated to security, compliance, and real-life success stories that demonstrate the transformative impact of cloud-based ML across various industries.
With practical guides, strategic insights, and current industry standards, this book is your roadmap to mastering cloud machine learning APIs, paving the way for innovative solutions that enhance competitiveness and efficiency. Embrace the future of artificial intelligence with this expertly crafted resource at your fingertips.
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Machine Learning Practical for Beginners: Practical Approach to Master Machine Learning
English | 2023 | ASIN: B0C1ZZKLWN | 346 pages | Epub | 7.09 MB
Python is often used for web development, data analysis, artificial intelligence, scientific computing, and automation tasks, among other things. It has a wide range of built-in libraries that make it easy to perform everyday functions without writing a lot of code.
In this book you will learn:
1. Logistic Regression
2. Build a Recommendation Engine With Collaborative Filtering
3. Three Ways of Storing and Accessing Lots of Images
4. Traditional Face Detection
5. Setting Up Python for Machine Learning on Windows
6. Practical Text Classification With Python and Keras
7. Image Segmentation Using Color Spaces in OpenCV + Python
8. Pure Python vs NumPy vs TensorFlow Performance Comparison
9. The Ultimate Guide To Speech Recognition
10. Fingerprinting Images for Near-Duplicate Detection
11. Face Detection in Python Using a Webcam
12. Face Recognition with Python
Overall, Python is an excellent choice for anyone who wants to learn programming, whether you're interested in web development, data analysis or want to learn a new skill. With its simplicity, readability, and versatility, Python is an excellent language to start your programming journey.
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Machine Learning Security with Azure: Best practices for assessing, securing, and monitoring Azure Machine Learning workloads
English | 2023 | ISBN: B0C466C36S | Pages: 432 | EPUB (True) | 11.06 MB
With AI and machine learning (ML) models gaining popularity and integrating into more and more applications, it is more important than ever to ensure that models perform accurately and are not vulnerable to cyberattacks. However, attacks can target your data or environment as well. This book will help you identify security risks and apply the best practices to protect your assets on multiple levels, from data and models to applications and infrastructure.
This book begins by introducing what some common ML attacks are, how to identify your risks, and the industry standards and responsible AI principles you need to follow to gain an understanding of what you need to protect. Next, you will learn about the best practices to secure your assets. Starting with data protection and governance and then moving on to protect your infrastructure, you will gain insights into managing and securing your Azure ML workspace. This book introduces DevOps practices to automate your tasks securely and explains how to recover from ML attacks. Finally, you will learn how to set a security benchmark for your scenario and best practices to maintain and monitor your security posture.
By the end of this book, you'll be able to implement best practices to assess and secure your ML assets throughout the Azure Machine Learning life cycle.
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Machine Learning: Unlocking the Power of Artificial Intelligence and How Algorithms Are Transforming Industries and Shaping Our Future
English | 2025 | ISBN: 9798231510405 | Pages: 106 | EPUB (True) | 551.29 KB
Unlock the Future with Machine Learning: Transforming Industries and Shaping Tomorrow
Are you ready to dive into the world of artificial intelligence and machine learning? Many feel overwhelmed by the complex jargon and rapid advancements in technology, but this book breaks it down for you in a clear and accessible way. Whether you're a beginner or looking to expand your knowledge, discover how machine learning is revolutionizing industries and changing our daily lives.
About This Book
Understand the fundamental concepts of machine learning and AI in simple terms.
Learn how machine learning algorithms transform industries like healthcare, finance, and transportation.
Discover real-world applications and examples of AI in action, from autonomous vehicles to personalized medicine.
Gain insight into the ethical challenges and future implications of AI technologies.
Explore how machine learning is helping businesses make data-driven decisions and improve efficiency.
Enhance your understanding of how AI is shaping the future of work, education, and communication.
Unlock the secrets of the digital age and stay ahead of the curve. Buy now and start your journey into the world of machine learning!
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Machine Learning with Python: Building Smart Systems for the Real World
English | 2025 | ISBN: B0F38CX7JY | Pages: 1242 | Epub | 22.59 MB
Machine Learning with Python - Building Smart Systems for the Real World
Turn data into decisions, and code into intelligent systems.
Whether you're a student, professional, or complete beginner, this book is your hands-on guide to mastering Python and building real-world machine learning applications from scratch-without getting lost in theory.
Machine Learning with Python: Building Smart Systems for the Real World is more than a technical manual-it's a learning journey. It starts with the very basics of Python and takes you all the way to building, evaluating, and deploying full-scale machine learning models using real datasets and real tools.
What You'll Learn:
Python from the Ground Up
Start with a solid foundation. Learn Python programming in a way that's simple, intuitive, and perfectly aligned with machine learning needs. Strings, lists, sets, tuples, dictionaries, and more-explained clearly and applied practically.
Smart Environment Setup
Get your machine learning lab ready. Work with Jupyter Notebooks, Anaconda, VSCode, Google Colab, and GitHub. Learn how to set up, manage, and version your code like a pro.
Data Preprocessing and Exploration
Clean, transform, and explore real-world datasets using Pandas and NumPy. Learn how to handle missing values, categorical variables, duplicates, and more.
Data Visualization
Use MatDescriptionlib and Seaborn to turn data into clear, compelling visuals. Description distributions, trends, relationships, and dashboards that make insights visible and decisions easier.
Core Machine Learning Concepts
Understand the full ML pipeline: supervised and unsupervised learning, classification and regression, performance metrics, model training, and evaluation. No heavy math-just clear explanations and working code.
Real-World Projects
Put theory into action with projects like:
Predicting used car prices
Assessing wine quality from physicochemical data
Forecasting insurance charges
Exploring agricultural datasets
Each project includes a step-by-step walkthrough and GitHub support for hands-on practice.
Model Deployment Made Simple
Learn to deploy models using Streamlit, Flask, and FastAPI. Understand how to make your models accessible, testable, and production-ready-even in the cloud.
Practice Challenges with Solutions
Every chapter includes exercises, mini-projects, and detailed solutions to reinforce your learning and build your confidence.
Who This Book Is For:
Students and beginners exploring machine learning for the first time
Career switchers and analysts looking to upskill with Python and AI
Developers and engineers expanding into the ML landscape
Educators and instructors who want a practical classroom resource
Anyone curious about how smart systems are built and deployed today
Machine learning is transforming industries-from healthcare and finance to transportation and marketing. But it's not just for experts in labs or PhDs with deep statistical backgrounds. With the right tools and a project-driven approach, you can build systems that learn, adapt, and make decisions.
This book gives you everything you need to get started-and to keep going.
Clear explanations. Real datasets. Code you can trust. Tools used by professionals. Whether you want to automate a process, power a product, or start a new career in AI, Machine Learning with Python: Building Smart Systems for the Real World will show you how.
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Machine Learning with PyTorch: From Basics to Expert Proficiency
English | 2024 | ISBN: B0DDXXKQ2S | Pages: 480 | EPUB (True) | 482.45 KB
"Machine Learning with PyTorch: From Basics to Expert Proficiency" is an indispensable guide for anyone aspiring to master the art and science of machine learning using PyTorch, one of the most powerful and flexible frameworks available today. This meticulously crafted book offers a comprehensive journey through the fundamental principles and advanced techniques of machine learning. From setting up your development environment to deploying sophisticated models, every chapter is designed to build your skills progressively, ensuring a deep understanding of both theoretical concepts and practical implementations.
Whether you are a beginner taking your first steps into the world of machine learning or an experienced practitioner looking to enhance your expertise, this book addresses your needs. Key topics include essential tensor operations, neural network construction, and advanced subjects such as Convolutional and Recurrent Neural Networks, transfer learning, and model deployment. With clear explanations, hands-on examples, and best practices, "Machine Learning with PyTorch" equips you with the knowledge and tools needed to tackle real-world challenges and innovate in various domains using machine learning.
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Machine Minds AI for all: An Ethical Intelligence & Responsible Revolution
English | 2024 | ISBN: 2940180755773 | Pages: 350 | EPUB (True) | 338.21 KB
Dive into the transformative power of Artificial Intelligence! From revolutionizing healthcare diagnostics to optimizing supply chains and personalized learning, this guide explores how AI shapes modern life, industries, and the future. Get insights on trends, ethical considerations, and the exciting potential of AI to enhance everyday experiences
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Machine Vision and Augmented Intelligence: Select Proceedings of MAI 2022 by Koushlendra Kumar Singh, Manish Kumar Bajpai, Akbar Sheikh Akbari
English | EPUB | 2023 | 645 Pages | ISBN : 981990188X | 136.5 MB
This book comprises the proceedings of the International Conference on Machine Vision and Augmented Intelligence (MAI 2022). The conference proceedings encapsulate the best deliberations held during the conference. The diversity of participants in the event from academia, industry, and research reflects in the articles appearing in the book. The book encompasses all industrial and non-industrial applications. This book covers a wide range of topics such as modeling of disease transformation, epidemic forecast, image processing, and computer vision, augmented intelligence, soft computing, deep learning, image reconstruction, artificial intelligence in health care, brain-computer interface, cybersecurity, social network analysis, and natural language processing.
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