Download or read book Mastering Machine Learning A Comprehensive Guide to Success written by Rick Spair and published by Rick Spair. This book was released on with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to "Mastering Machine Learning: A Comprehensive Guide to Success." In this book, we embark on an exciting journey into the world of machine learning (ML), exploring its concepts, techniques, and practical applications. Whether you are a beginner taking your first steps into the field or an experienced practitioner seeking to deepen your knowledge, this comprehensive guide will equip you with the tools, strategies, and insights needed to succeed in the ever-evolving landscape of ML. Machine learning is a rapidly advancing field that has revolutionized industries and transformed the way we tackle complex problems. From personalized recommendations and speech recognition systems to autonomous vehicles and medical diagnostics, machine learning has become an integral part of our daily lives. Its ability to analyze vast amounts of data, identify patterns, and make predictions has paved the way for groundbreaking advancements across various domains. However, mastering machine learning requires more than just understanding the algorithms and techniques. It requires a holistic approach that encompasses data collection and preparation, exploratory data analysis, model building, evaluation, deployment, and continuous learning. It also demands a deep understanding of the ethical and social implications of machine learning, ensuring responsible and fair use of this powerful technology. In this book, we have carefully crafted 20 comprehensive chapters that cover a wide range of topics, from the fundamentals of machine learning to advanced techniques and future trends. Each chapter provides a deep dive into a specific aspect of machine learning, offering tips, recommendations, and strategies for success. You will learn about various algorithms, data preprocessing techniques, model evaluation methods, interpretability approaches, and much more. Throughout the book, we emphasize a practical approach to machine learning. Real-world examples, case studies, and hands-on exercises are incorporated to help you gain a deeper understanding of the concepts and apply them to your own projects. We believe that active learning and practical experience are crucial for mastering machine learning, and we encourage you to explore, experiment, and build your own models. While this book serves as a comprehensive guide, it is important to note that machine learning is a rapidly evolving field. New algorithms, techniques, and technologies are constantly emerging, and staying up-to-date with the latest advancements is essential. However, the principles and foundations discussed in this book will provide you with a solid framework to adapt and navigate the ever-changing landscape of machine learning. Whether you are an aspiring data scientist, a software engineer, a researcher, or a business professional, this book is designed to be your trusted companion in your journey to mastering machine learning. By the time you reach the end, you will have gained a deep understanding of the fundamental concepts, acquired practical skills for applying machine learning in real-world scenarios, and developed the mindset needed to tackle complex challenges and drive innovation. Get ready to embark on an exciting adventure into the world of machine learning. Let's begin our journey towards mastering machine learning and unlocking its full potential. Happy learning!

Download or read book Mastering Machine Learning A Comprehensive Guide to Success written by Rick Spair and published by Rick Spair. This book was released on with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to "Mastering Machine Learning: A Comprehensive Guide to Success." In this book, we embark on an exciting journey into the world of machine learning (ML), exploring its concepts, techniques, and practical applications. Whether you are a beginner taking your first steps into the field or an experienced practitioner seeking to deepen your knowledge, this comprehensive guide will equip you with the tools, strategies, and insights needed to succeed in the ever-evolving landscape of ML. Machine learning is a rapidly advancing field that has revolutionized industries and transformed the way we tackle complex problems. From personalized recommendations and speech recognition systems to autonomous vehicles and medical diagnostics, machine learning has become an integral part of our daily lives. Its ability to analyze vast amounts of data, identify patterns, and make predictions has paved the way for groundbreaking advancements across various domains. However, mastering machine learning requires more than just understanding the algorithms and techniques. It requires a holistic approach that encompasses data collection and preparation, exploratory data analysis, model building, evaluation, deployment, and continuous learning. It also demands a deep understanding of the ethical and social implications of machine learning, ensuring responsible and fair use of this powerful technology. In this book, we have carefully crafted 20 comprehensive chapters that cover a wide range of topics, from the fundamentals of machine learning to advanced techniques and future trends. Each chapter provides a deep dive into a specific aspect of machine learning, offering tips, recommendations, and strategies for success. You will learn about various algorithms, data preprocessing techniques, model evaluation methods, interpretability approaches, and much more. Throughout the book, we emphasize a practical approach to machine learning. Real-world examples, case studies, and hands-on exercises are incorporated to help you gain a deeper understanding of the concepts and apply them to your own projects. We believe that active learning and practical experience are crucial for mastering machine learning, and we encourage you to explore, experiment, and build your own models. While this book serves as a comprehensive guide, it is important to note that machine learning is a rapidly evolving field. New algorithms, techniques, and technologies are constantly emerging, and staying up-to-date with the latest advancements is essential. However, the principles and foundations discussed in this book will provide you with a solid framework to adapt and navigate the ever-changing landscape of machine learning. Whether you are an aspiring data scientist, a software engineer, a researcher, or a business professional, this book is designed to be your trusted companion in your journey to mastering machine learning. By the time you reach the end, you will have gained a deep understanding of the fundamental concepts, acquired practical skills for applying machine learning in real-world scenarios, and developed the mindset needed to tackle complex challenges and drive innovation. Get ready to embark on an exciting adventure into the world of machine learning. Let's begin our journey towards mastering machine learning and unlocking its full potential. Happy learning!

Download or read book Machine Learning for Beginners written by Ryan Knight and published by Ryan Knight. This book was released on 2024-05-08 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enter a world of algorithms, data, and artificial intelligence, this all-inclusive guide strips away the complexity of machine learning and AI, transforming them from daunting subjects into accessible and comprehendible concepts. Whether you're a total novice or a professional looking to broaden your knowledge, this guide provides a structured approach that walks you through the basics, right through to the cutting-edge applications of AI and machine learning. Crafted with the reader in mind, every chapter provides detailed explanations, relatable examples, and step-by-step instructions to ensure a comprehensive yet enjoyable learning experience. Inside this book, you'll discover: An introduction to the exciting world of machine learning and AI, making it accessible to everyone regardless of technical background. Comprehensive discussions on the foundational concepts of machine learning, including algorithms, data science principles, and the different types of machine learning. Deep dives into the transformative applications of AI and machine learning in industries such as healthcare, retail, finance, transportation, education, and entertainment. Practical guides on mastering the essential tools and techniques for building intelligent solutions, complete with hands-on exercises and examples. An exploration of the ethical considerations around AI and machine learning, and the responsibilities we have as practitioners. Future trends in machine learning and AI, providing a glimpse into what lies on the horizon. Ignite your journey into the fascinating world of machine learning and AI today. Unleash the power of data and algorithms, create intelligent solutions, and shape a better future. Are you ready to master the future? The opportunity is just a click away. Pick up your copy now, and let's get started!

Download or read book Mastering Machine Learning with Core ML and Python written by Vardhan Agrawal and published by AppCoda. This book was released on 2020-08-13 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning, now more than ever, plays a pivotal role in almost everything we do in our digital lives. Whether it’s interacting with a virtual assistant like Siri or typing out a message to a friend, machine learning is the technology facilitating those actions. It’s clear that machine learning is here to stay, and as such, it’s a vital skill to have in the upcoming decades. This book covers Core ML in-depth. You will learn how to create and deploy your own machine learning model. On top of that, you will learn about Turi Create, Create ML, Keras, Firebase, and Jupyter Notebooks, just to name a few. These are a few examples of professional tools which are staples for many machine learning experts. By going through this book, you’ll also become proficient with Python, the language that’s most frequently used for machine learning. Plus, you would have created a handful of ready-to-use apps such as barcode scanners, image classifiers, and language translators. Most importantly, you will master the ins-and-outs of Core ML.

Download or read book Practical Machine Learning with Python written by Dipanjan Sarkar and published by Apress. This book was released on 2017-12-22 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries and frameworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students

Download or read book Mastering Machine Learning written by Cybellium Ltd and published by Cybellium Ltd. This book was released on 2023-09-05 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to become a master of machine learning? In "Mastering Machine Learning" by Kris Hermans, you'll embark on a transformative journey that will empower you with the skills and knowledge needed to conquer the world of data-driven intelligence. Discover Cutting-Edge Techniques and Practical Applications From self-driving cars to personalized recommendations, machine learning is transforming industries and reshaping the way we live and work. In this comprehensive guide, Kris Hermans equips you with the tools to harness the power of machine learning. Dive into the core concepts, algorithms, and models that underpin this revolutionary field. Become a Proficient Practitioner Whether you're a beginner or an experienced professional, this book provides a clear and structured path to mastering machine learning. Through hands-on examples and real-world case studies, you'll gain practical expertise in implementing machine learning models and solving complex problems. Kris Hermans guides you through the process, ensuring you develop a deep understanding of the techniques and algorithms that drive intelligent systems. From Fundamentals to Advanced Topics "Mastering Machine Learning" covers the full spectrum of machine learning, starting with the foundations of supervised and unsupervised learning and progressing to reinforcement learning, neural networks, and deep learning. Explore diverse models and learn how to choose the right approach for different applications. With this knowledge, you'll be able to tackle real-world challenges with confidence. Unlock the Potential of Machine Learning Across Industries Discover how machine learning is revolutionizing industries such as finance, healthcare, e-commerce, and cybersecurity. Through captivating case studies, you'll witness the transformative impact of machine learning and gain insights into how organizations are leveraging this technology to drive innovation, improve decision-making, and achieve unprecedented success. Navigate Ethical Considerations As machine learning becomes increasingly powerful, it's crucial to consider the ethical implications. "Mastering Machine Learning" addresses these important considerations head-on. Learn about the ethical challenges and responsibilities associated with machine learning applications and gain the knowledge to make informed, ethical decisions in your own work.

Download or read book Deep Learning written by Shriram K Vasudevan and published by CRC Press. This book was released on 2021-12-24 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning (DL) and Machine Learning (ML) concepts. DL and ML are the most sought-after domains, requiring a deep understanding – and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and DL. Starting with the basics of neural networks, and continuing through the architecture of various types of CNNs, RNNs, LSTM, and more till the end of the book, each and every topic is given the utmost care and shaped professionally and comprehensively. Key Features Includes the smooth transition from ML concepts to DL concepts Line-by-line explanations have been provided for all the coding-based examples Includes a lot of real-time examples and interview questions that will prepare the reader to take up a job in ML/DL right away Even a person with a non-computer-science background can benefit from this book by following the theory, examples, case studies, and code snippets Every chapter starts with the objective and ends with a set of quiz questions to test the reader’s understanding Includes references to the related YouTube videos that provide additional guidance AI is a domain for everyone. This book is targeted toward everyone irrespective of their field of specialization. Graduates and researchers in deep learning will find this book useful.

Download or read book Mastering Machine Learning written by Dr Hesham Mohamed Elsherif and published by . This book was released on 2024-03-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to "Mastering Machine Learning: A Comprehensive Guide to Language and Practice." In today's rapidly evolving technological landscape, the ability to harness the power of machine learning has become paramount. Whether you're a seasoned programmer looking to delve into the intricacies of artificial intelligence or a newcomer eager to explore the realm of data-driven decision-making, this book is your gateway to mastering the language of machine learning. Machine learning, with its ability to extract insights from vast amounts of data and make predictions with remarkable accuracy, has revolutionized countless industries, from healthcare to finance, from retail to transportation. However, mastering machine learning entails more than just understanding algorithms and writing code. It requires a solid foundation in programming languages, a deep understanding of mathematical concepts, and a keen intuition for problem-solving. This book is designed to be your comprehensive companion on this journey of discovery. From the fundamentals of programming languages to the intricacies of deep learning, each chapter is crafted to provide you with the knowledge and skills necessary to navigate the complex landscape of machine learning. Whether you're interested in supervised learning algorithms, unsupervised learning techniques, or the latest advancements in deep learning, you'll find a wealth of information to guide you along the way. But this book is more than just a collection of theories and algorithms. It's a hands-on guide that empowers you to apply what you've learned to real-world problems. With practical examples, code snippets, and case studies, you'll learn not only how to build machine learning models but also how to evaluate their performance, fine-tune their parameters, and deploy them in production environments. Moreover, as we explore the fascinating world of machine learning, we cannot ignore the ethical implications of our work. From concerns about bias and fairness to questions of privacy and security, this book encourages you to consider the ethical dimensions of machine learning and to approach your work with integrity and responsibility. Whether you're a student, a researcher, a data scientist, or simply a curious mind eager to explore the frontiers of artificial intelligence, "Mastering Machine Learning" is your guidebook to unlocking the full potential of machine learning. So, dive in, embrace the challenges, and embark on this exhilarating journey into the heart of machine intelligence. Happy learning! Dr. Hesham Mohamed Elsherif

Download or read book Building Machine Learning and Deep Learning Models on Google Cloud Platform written by Ekaba Bisong and published by Apress. This book was released on 2019-09-27 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. What You’ll Learn Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your resultsKnow the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products Who This Book Is For Beginners to the practice of data science and applied machine learning, data scientists at all levels, machine learning engineers, Google Cloud Platform data engineers/architects, and software developers

Download or read book Mastering Machine Learning with R Second Edition written by Cory Lesmeister and published by . This book was released on 2017-04-20 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning techniques with R to deliver insights in complex projectsAbout This Book- Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST- Understand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised Learning- Implement advanced concepts in machine learning with this example-rich guideWho This Book Is ForThis book is for data science professionals, data analysts, or anyone with a working knowledge of machine learning, with R who now want to take their skills to the next level and become an expert in the field.What You Will Learn- Gain deep insights into the application of machine learning tools in the industry- Manipulate data in R efficiently to prepare it for analysis- Master the skill of recognizing techniques for effective visualization of data- Understand why and how to create test and training data sets for analysis- Master fundamental learning methods such as linear and logistic regression- Comprehend advanced learning methods such as support vector machines- Learn how to use R in a cloud service such as AmazonIn DetailThis book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you'll understand how these concepts work and what they do.With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.Style and approachThe book delivers practical and real-world solutions to problems and a variety of tasks such as complex recommendation systems. By the end of this book, you will have gained expertise in performing R machine learning and will be able to build complex machine learning projects using R and its packages.

Download or read book Mastering Machine Learning Basics written by Moss Adelle Louise and published by Moss Adelle Louise. This book was released on 2024-03-19 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you fascinated by the endless possibilities that Machine Learning offers? Do you want to unlock the secrets behind this transformative technology and harness its power for your own projects? Look no further! "Mastering Machine Learning Basics: A Beginner's Companion" is the ultimate guide for individuals who are eager to dive into the world of machine learning and gain the essential skills needed to navigate this exciting field. In this comprehensive book, we have carefully crafted a step-by-step journey that clears the fog surrounding machine learning, making it accessible and easy to understand, even for those with no prior experience. Our simplified yet insightful approach ensures that learners, regardless of their background, can gain a solid understanding of the foundations of machine learning in record time. Written with the curious and enthusiastic beginner in mind, "Mastering Machine Learning Basics" provides a gentle introduction without overwhelming technical jargon. We firmly believe that a solid understanding of core concepts is crucial for mastering any subject, and thus we start by covering the fundamental principles of machine learning. From here, we seamlessly progress through key topics, allowing you to steadily build upon your newfound knowledge. Inside these pages, you will embark on an exciting learning journey that covers a wide array of essential topics. Our carefully curated chapters provide clarity on various machine learning algorithms, ensuring you fully comprehend their mechanics and how they can be applied in real-world scenarios. This book focuses on demystifying common algorithms like linear regression, support vector machines, ensemble methods, and neural networks, among others. We fully comprehend the importance of hands-on experience in mastering any subject. That's why we included practical examples, illustrative diagrams, and interactive exercises throughout the book. These aids not only reinforce your understanding but also enable you to apply what you've learned to solve real-world problems. You'll become an active participant in your learning journey, actively developing your skills while simultaneously building a strong foundation of knowledge. No book on machine learning would be complete without ensuring a comprehensive understanding of the evaluation and validation methods necessary for measuring true success. We dedicate a significant portion of the book to teach you how to confidently evaluate the effectiveness and generalization capabilities of your trained models to ensure their reliability. But it certainly doesn't end there! In "Mastering Machine Learning Basics," we go the extra mile to provide you with valuable tips, tricks, and best practices. You will gain a broad understanding, not just of machine learning concepts, but of the entire journey, from preprocessing your data to choosing the right algorithm, solving common challenges, handling overfitting, and exploring big data approaches.

Download or read book Machine Learning with Python written by Steve Blair and published by Steve Blair. This book was released on 2021-04-16 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge your Python skills and uncover the amazing benefits of machine learning with this complete guide. Are you a newcomer to the incredible programming language of Python? Are you searching for a practical beginner's introduction to the world of machine learning, artificial intelligence, and how you can create your own neural networks? Then it's time to try this book! Machine learning is the way of the future, and as a programmer, it's never been more important to understand this groundbreaking concept and begin creating your own neural networks. So how can you begin mastering machine learning even if you have only a basic understanding of Python? Packed with handy advice and detailed overviews, Python Machine Learning unveils the inner workings of neural networks and artificial intelligence in a way that even beginners can understand. With reference to basic terminology and concepts, training sets, algorithms, and so much more, this complete guide lets you begin creating your own networks even with the most basic knowledge of Python. Plus, you'll also find a wealth of tips for building good data sets and finding the right algorithm for all of your goals. Inside this comprehensive guide, you'll find: A Brilliant Introduction To The Essentials of Machine Learning and Its Surprising History Understanding The Basic Terminology and Ideas Behind Machine Learning Systems How To Pick The Right Classifiers, Variables, Metrics, Models, and More Practical Advice For Developing Your Own Machine Learning System 10 Must-Know Algorithms For Classification Tips and Tricks For Building Good Data Sets And Much More... Whether you want to begin programming for the first time, expand your skillsets into new areas, or simply create artificial intelligence as a hobby, Python Machine Learning shows you in plain English how to supercharge your Python skills and begin experimenting with this revolutionary programming concept. Buy now to begin creating neural networks today

Download or read book Machine Learning for Beginners written by Samuel Hack and published by Samuel Hack. This book was released on 2021-03-07 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: TODAY ONLY 55% OFF for Bookstores! Are you interested in learning about the amazing capabilities of machine learning, but you're worried it will be just too complicated? Or are you a programmer looking for a solid introduction into this field? Your customers must have this guide to understand the hidden secrets of artificial intelligence! Machine learning is an incredible technology which we're only just beginning to understand. Those who break into this industry early will reap the rewards as this field grows more and more important to businesses the world over. And the good news is, it's not too late to start! This guide breaks down the fundamentals of machine learning in a way that anyone can understand. With reference to the different kinds of machine learning models, neural networks, and the way these models learn data, you'll find everything you need to know to get started with machine learning in a concise, easy-to-understand way. Here's what you'll discover inside: What is Artificial Intelligence Really, and Why is it So Powerful? Choosing the Right Kind of Machine Learning Model for You An Introduction to Statistics Supervised and Unsupervised Learning The Power of Neural Networks Reinforcement Learning and Ensemble Modeling "Random Forests" and Decision Trees Must-Have Programming Tools And Much More! Whether you're already a programmer or if you're a complete beginner, now you can break into machine learning in no time! Covering all the basics from simple decision trees to the complex decision-making processes which mirror our own brains, Machine Learning for Beginners is your comprehensive introduction to this amazing field! Buy it NOW and let your customers become to addicted to this incredible book!

Download or read book Mastering Deep Learning Fundamentals written by Ai Publishing and published by AI Publishing. This book was released on 2019-06-09 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: ** ONE HOUR FREE VIDEO COURSE IN DEEP LEARNING INCLUDED** **Get your copy now, the price will change soon**You are interested in deep learning, but don't know how to get startedLet us help youWho are the book for? Are a college student and want more than your university course offers Are you a student interested in a career in Data science? Are you a programmer who wants to make a career switch into data science and AI? Are you an engineer who wants to use new data science techniques at your current job? Are you an entrepreneur who dreams of a data science but do not yet know the basics? Are you a hobbyist who wants to build cool data science projects? Are you a data scientist practitioner and want to broaden your area of expertise? If the answer to any of the above questions is a YES, this book is for you.We have designed this book for beginners in mind and our goal is to prepare students with practical skills to solve real-world problems and to stand out in the job market.This book are not for shallow learners who simply want to copy-paste code. This book will require your time and commitment.Our book is different from other books?If you are searching for a step by step guide to learn deep learning and AI from scratch or are interested in the current updates of the AI world, our book is just the right one for you. This book paves beginners' road towards the path of deep learning concepts and algorithms without any traditional complexity of mathematical formulas.With the help of graphs and images, this books is the easiest to comprehend even by those who have no previous technological knowledge of machine learning. Moreover, our book, with its comprehensive content, prepares the readers for higher advanced courses.We strive to provide world-class data science and AI education at reasonable prices. To achieve that, we have put in a lot of planning and efforts to provide a rich learning experience for the students.What's Inside This Book? Part I: Fundamentals of Deep learning Fundamentals of Probability Fundamentals of Statistics Fundamentals of Linear Algebra Introduction to Machine Learning and Deep Learning Fundamentals of Machine Learning Fundamentals of Neural Networks and Deep Learning Deep Learning Parameters and Hyper-parameters Deep Neural Networks Layers Deep Learning Activation Functions Deep Learning Loss Functions Deep Learning Optimization Algorithms Convolutional Neural Network Recurrent Neural Networks LSTM Recursive Neural Networks Bonus Course Conclusion Part II: Deep Learning in Practice (In Jupyter notebooks) Python for Beginners Python Data Structures Python Function Object Oriented Programming in Python Best practices in Python and Zen of Python Installing Python Numpy, Pandas, Matplotlib and Scikit-learn Evaluating a model's performance Keras and Tensorflow Deep learning workstation: Jupyter Notebooks and Getting Binary Classification Building Deep Learning Model Convolutional Neural Networks in Keras Data Preparation Model Building Training and Testing Deep learning for text and sequences Brief introduction to Google Colab Data Preparation Data Wrangling and Analysis Recurrent Neural Network (RNN) ** MONEY BACK GUARANTEE BY AMAZON **If you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform or contact us (our email inside the book).

Download or read book Mastering Machine Learning Practical Applications Across Industries written by Vijay Gupta and published by eInitial Publication. This book was released on 2024-05-08 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mastering Machine Learning: Practical Applications Across Industries" offers a comprehensive exploration of the transformative potential of machine learning (ML) across diverse sectors. From healthcare to finance, manufacturing to entertainment, this ebook delves into the practical applications and real-world case studies that showcase the power of ML in driving innovation and efficiency. Through a blend of theoretical insights and hands-on guidance, readers will embark on a journey through the fundamentals of ML techniques, understanding key concepts, algorithms, and methodologies. The ebook illuminates the path from theory to practice, providing actionable strategies for implementing ML solutions in various organizational contexts. Each chapter is carefully crafted to highlight the unique challenges and opportunities present in different industries, offering in-depth analyses of successful ML implementations and the lessons learned along the way. From predicting patient outcomes in healthcare to optimizing financial portfolios in banking, readers will discover how ML is revolutionizing decision-making processes and reshaping business landscapes. Moreover, "Mastering Machine Learning" doesn't shy away from addressing the ethical considerations inherent in ML applications. Discussions on bias, fairness, privacy, and transparency provide readers with a nuanced understanding of the social and ethical implications of ML adoption, empowering them to navigate these complex issues responsibly. Whether you're a seasoned data scientist looking to expand your expertise or a business leader seeking to leverage ML for strategic advantage, this ebook serves as an indispensable guide. Packed with insights, case studies, and practical tips, "Mastering Machine Learning" equips readers with the knowledge and tools needed to harness the full potential of ML across industries and drive meaningful impact in an increasingly data-driven world.

Download or read book Machine Learning and Robotics written by Albert Torres and published by Albert Torres. This book was released on 2021-04-19 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: !! 55% OFF for Bookstores!! NOW at 33.95 instead of 43.95 !! Buy it NOW and let your customers get addicted to this awesome book!

Download or read book Machine Learning written by Samuel Hack and published by . This book was released on 2021-01-07 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the world of Python and Machine Learning with this incredible 4-in-1 bundle. Are you interested in becoming a Python pro?Do you want to learn more about the incredible world of machine learning, and what it can do for you? Then keep reading. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and Machine Learning, from basic code and mathematical formulas to complex neural networks and ensemble modeling. Inside, you'll discover everything you need to know to get started with Python and Machine Learning, and begin your journey to success! In book one - MACHINE LEARNING FOR BEGINNERS, you'll learn: What is Artificial Intelligence Really, and Why is it So Powerful? Choosing the Right Kind of Machine Learning Model for You An Introduction to Statistics Reinforcement Learning and Ensemble Modeling "Random Forests" and Decision Trees In book two - MACHINE LEARNING MATHEMATICS, you will: Learn the Fundamental Concepts of Machine Learning Algorithms Understand The Four Fundamental Types of Machine Learning Algorithm Master the Concept of "Statistical Learning" Learn Everything You Need to Know about Neural Networks and Data Pipelines Master the Concept of "General Setting of Learning" In book three - LEARNING PYTHON, you'll discover: How to Install, Run, and Understand Python on Any Operating System A Comprehensive Introduction to Python Python Basics and Writing Code Writing Loops, Conditional Statements, Exceptions and More Python Expressions and The Beauty of Inheritances And in book four - PYTHON MACHINE LEARNING, you will: Learn the Fundamentals of Machine Learning Master the Nuances of 12 of the Most Popular and Widely-Used Machine Learning Algorithms Become Familiar with Data Science Technology Dive Into the Functioning of Scikit-Learn Library and Develop Machine Learning Models Uncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets Whether you're a complete beginner or a programmer looking to improve your skillset, this bundle is your all-in-one solution to mastering the world of Python and Machine Learning. So don't wait - it's never been easier to learn. Buy Now to Become a Master of Python and Machine Learning Today!