Machine Learning Made Simple
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Machine Learning Made Simple
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Author : Daniel Lee
language : en
Publisher: Daniel Lee
Release Date : 2025-01-22
Machine Learning Made Simple written by Daniel Lee and has been published by Daniel Lee this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.
"Machine Learning Made Simple: A Practical Introduction: Building Intelligent Algorithms from Scratch" is your go-to resource for comprehending and using machine learning without becoming bogged down in overwhelming complexity or technical jargon. This book, which simplifies the principles of machine learning and provides practical possibilities to develop clever algorithms step-by-step, is ideal for novices and inquisitive learners. The book begins by outlining the fundamental ideas, including supervised and unsupervised learning, and then it progressively guides you through the crucial steps involved in managing data, including cleaning, preprocessing, and visualizing it in order to derive insightful information. You will gain a comprehension of the theory and the ability to apply it on your own by learning how to build fundamental algorithms like linear regression from scratch with an emphasis on practicality. The book provides real-world examples and a case study where you will construct and assess a basic prediction model to further humanize the concepts. As you advance, you'll also discover how to enhance model performance and switch to specialized tools like Scikit-learn, which will allow you to expand your knowledge and skills. This book will enable you to understand the principles and begin developing clever solutions, regardless of whether you're a professional, tech enthusiast, or student interested in machine learning. Take the first step toward becoming an expert in machine learning by diving right in!
Project Based Learning Made Simple
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Author : April Smith
language : en
Publisher: Simon and Schuster
Release Date : 2018-05-08
Project Based Learning Made Simple written by April Smith and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Education categories.
100 ready-to-use projects to challenge and inspire your third-, fourth- and fifth-graders! Project Based Learning Made Simple is the fun and engaging way to teach twenty-first-century competencies including problem solving, critical thinking, collaboration, communication and creativity. This straightforward book makes it easier than ever to bring this innovative technique into your classroom with 100 ready-to-use projects in a range of topics, including: Science and STEM • Save the Bees! • Class Aquarium • Mars Colony Math Literacy • Personal Budgeting • Bake Sale • Family Cookbook Language Arts • Candy Bar Marketing • Modernize a Fairy Tale • Movie Adaptation Social Studies • Build a Statue • Establish a Colony • Documenting Immigration
Machine Learning Made Simple
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Author : Greyson Chesterfield
language : en
Publisher: Independently Published
Release Date : 2025-03-13
Machine Learning Made Simple written by Greyson Chesterfield and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-13 with Computers categories.
Machine Learning Made Simple: Master AI Algorithms Without Complex Math is the ultimate beginner-friendly guide to understanding and applying machine learning (ML) and AI algorithms without the need for complicated mathematics. Whether you're just starting your data science journey or looking to enhance your skills, this book breaks down key concepts in a simple, easy-to-understand format, making machine learning accessible to everyone. Through clear explanations, practical examples, and intuitive illustrations, you'll learn how to implement data science and machine learning techniques for predictive modeling, deep learning, and more-without the need for advanced math or programming knowledge. This book will empower you to apply machine learning to real-world problems and develop AI solutions in a user-friendly manner. Inside, you'll discover: Introduction to Machine Learning: Understand what machine learning is, its key concepts, and the different types of learning-supervised, unsupervised, and reinforcement learning-without diving into complex formulas. Data Science for Beginners: Learn the basics of data science, including data preprocessing, cleaning, and visualization, and how to prepare data for machine learning algorithms. Key Machine Learning Algorithms: Explore popular machine learning algorithms like linear regression, decision trees, k-nearest neighbors, and support vector machines, and how they can be used for predictive modeling. Building Your First Model: Get hands-on experience with building a machine learning model using Python libraries like Scikit-learn and understand how to train, test, and evaluate its performance. Deep Learning Simplified: Learn the fundamentals of deep learning and neural networks, with a focus on how deep learning models are trained to solve complex tasks like image recognition and natural language processing. Model Evaluation and Improvement: Discover how to evaluate the performance of machine learning models using metrics such as accuracy, precision, recall, and F1-score, and how to optimize models for better results. Unsupervised Learning and Clustering: Understand the concepts behind unsupervised learning, including clustering techniques like k-means, and how they can be used to group data without labels. Practical Machine Learning Applications: Learn how to apply machine learning to real-world use cases, such as recommendation systems, fraud detection, and predictive analytics. The Future of AI and Machine Learning: Gain insights into the future of AI and machine learning, including emerging trends like reinforcement learning, generative adversarial networks (GANs), and the ethical considerations of AI. By the end of this book, you'll have a solid understanding of machine learning principles and the confidence to build your own models, apply them to real-world problems, and continue your journey in the exciting field of AI and data science.
Healthcare Analytics Made Simple
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Author : Vikas (Vik) Kumar
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-07-31
Healthcare Analytics Made Simple written by Vikas (Vik) Kumar and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-31 with Computers categories.
Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
Machine Learning Explained A Practical Guide To Data Driven Decision Making
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Author : Abdelhamid ZAIDI
language : en
Publisher: Xoffencerpublication
Release Date : 2023-10-30
Machine Learning Explained A Practical Guide To Data Driven Decision Making written by Abdelhamid ZAIDI and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-30 with Computers categories.
During the course of the process of making a choice, we rely on a variety of presumptions, premises, and the circumstances; all of this is directed by the goal that is related with the decision itself. However, the premises and the knowledge of the corporation are dependent on our data since they are an essential component of our organization as a system. The context and the assumptions are both external factors that are beyond the control of any decision maker. Both the background and the assumptions represent outside forces that are not within the control of any decision maker. A prominent example of a conceptual error is the misunderstanding that exists between data and information, which in reality correspond to entirely distinct ideas. This misunderstanding is a common occurrence. In point of fact, information and data cannot in any way be substituted for one another in any context. To put this another way, there is no guarantee that the data will be consistent, comparable, or traceable, despite the fact that we are able to collect data from a broad variety of distinct data sources. This is because there are so many diverse data sources. Because of this, in order for us to make a decision, we need to have a good comprehension of both the component that is presently being examined and the data that is linked with it at the present time. Only then will we be able to make an informed choice. The identification of the system itself is the first step that must be taken before any other aspects of the system, such as its boundaries, context, subsystems, feedback, inputs, and outputs, can be determined. Because of this, it is significant because, according to the point of view connected with general system theory, it is necessary to identify the system that is being discussed. In order to get a more in-depth understanding of the system, we must first begin by defining it. After that, we may proceed to quantifying each associated quality in order to achieve this goal. This would make it possible for us to have a better understanding of the system. Because of this, in order for us to collect information on the topic of the research, we will initially need to measure it in order to quantify the characteristics that are associated with it. For this, we will need to perform certain measurements on the subject. After that, we will establish the indicators that will be applied for the purpose of determining the value of each measure, and we will do so by utilizing the results of the stage that came before it. Within the context of this method, the Measurement and Evaluation (M&E) process can gain an advantage from making use of a conceptual framework that is built on top of an underlying ontology. The M&E framework makes it possible to describe the basic ideas, which prepares the way for a measurement process to be carried out in a manner that is consistent and repeatable. This is made possible by the fact that the framework makes it possible to specify the essential concepts. The ability of a measuring process to be automated is of the utmost significance, even if it is required for a measuring process to give findings that are consistent, comparable, and traceable. The ability of a measuring process to be automated is of the utmost relevance. Because the activities that take place in today's economy take place in real time, we need to pay considerable attention to the use of online monitoring in order to notice and avoid a variety of different scenarios while they are happening. Because of this, we will be able to reduce risk while maximizing our efficiency. In this regard, the functionality of the measurement and evaluation frameworks is an extremely valuable asset, as they make it possible to organize and automate the process of measuring in a manner that is consistent. This makes the frameworks an exceptionally helpful asset. As a result of this, the frameworks are a very useful asset. As soon as it is feasible to guarantee that the measurements are comparable, consistent, and traceable, the method of decision-making will naturally be based on their history, which will consist of the measurements collected throughout the years. This will be the case as soon as it is possible to guarantee that the measurements are comparable, consistent, and traceable. This will take place as soon as it is practical to assure that the measurements are comparable, consistent, and traceable. In this regard, the organizational memory is of special importance due to the fact that it makes it possible to store prior organizational experience and knowledge in order to get ready for future proposals (that is, as the foundation for a range of different assumptions and premises, among other things). In this regard, the organizational memory is of particular use. Because of this, the organizational memory is a component that is of very high importance. Measurements and the experiences that are associated with them provide continuous nourishment for the organizational memory, and the organizational memory provides the foundation for the feedback that is utilized in the process of decision making.
Machine Learning Made Easy A Beginner S Guide For All
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Author : M.B. Chatfield
language : en
Publisher: M.B. Chatfield
Release Date :
Machine Learning Made Easy A Beginner S Guide For All written by M.B. Chatfield and has been published by M.B. Chatfield this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unleash the power of machine learning to automate tasks, make predictions, and solve complex problems. Machine learning is a powerful tool that can be used to automate tasks, make predictions, and solve complex problems. It is used in a wide variety of industries, including healthcare, finance, and manufacturing. Machine Learning Made Easy is the perfect resource for anyone who wants to learn the basics of machine learning. This comprehensive guide covers everything you need to know, from the basics of machine learning algorithms to advanced topics such as deep learning. Whether you're a student, a business professional, or a data enthusiast, Machine Learning Made Easy is the essential resource for learning about machine learning. Here are some of the key topics covered in the book: Introduction to machine learning Types of machine learning algorithms Choosing the right machine learning algorithm Training a machine learning model Evaluating a machine learning model Using machine learning to automate tasks Using machine learning to make predictions If you are a beginner who wants to learn about machine learning, Machine Learning Made Easy is a great place to start. #datascience #machinelearning #analyticsforeveryone #dataanalysisforbeginners #data #datavisualization #machinelearning #beginnersguide #learndata #GoogleAnalytics #Google #mobileapp #datavisualization #madeeasy #madesimple
Deep Learning Explained Theory Applications And Future Directions
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Author : ASHISH KUMAR , ABHISHEK DAS, SHYAMAKRISHNA SIDDHARTH CHAMARTHY, PROF. (DR) PUNIT GOEL
language : en
Publisher: DeepMisti Publication
Release Date : 2024-10-19
Deep Learning Explained Theory Applications And Future Directions written by ASHISH KUMAR , ABHISHEK DAS, SHYAMAKRISHNA SIDDHARTH CHAMARTHY, PROF. (DR) PUNIT GOEL and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-19 with Computers categories.
In the ever-evolving landscape of the modern world, the synergy between technology and management has become a cornerstone of innovation and progress. This book, Deep Learning Explained: Theory, Applications, and Future Directions, is conceived to bridge the gap between emerging technological advancements in artificial intelligence and their strategic application across various industries. Our objective is to equip readers with the tools and insights necessary to excel in this dynamic intersection of fields. This book is structured to provide a comprehensive exploration of the methodologies and strategies that define the innovation of deep learning technologies, from foundational theories to advanced applications. We delve into the critical aspects that drive successful AI innovations in fields such as healthcare, finance, e-commerce, and autonomous systems. We have made a concerted effort to present complex concepts in a clear and accessible manner, making this work suitable for a diverse audience, including students, researchers, and industry professionals. In authoring this book, we have drawn upon the latest research and best practices to ensure that readers not only gain a robust theoretical understanding but also acquire practical skills that can be applied in real-world scenarios. The chapters are designed to strike a balance between depth and breadth, covering topics ranging from technological development and AI adoption to the strategic management of deep learning innovations. Additionally, we emphasize the importance of effective communication, dedicating sections to the art of presenting innovative ideas and solutions in a precise and academically rigorous manner. The inspiration for this book arises from a recognition of the crucial role that deep learning and AI technologies play in shaping the future of industries and businesses. We are profoundly grateful to Chancellor Shri Shiv Kumar Gupta of Maharaja Agrasen Himalayan Garhwal University for his unwavering support and vision. His dedication to fostering academic excellence and promoting a culture of innovation has been instrumental in bringing this project to fruition. We hope this book will serve as a valuable resource and inspiration for those eager to deepen their understanding of how deep learning can be harnessed to drive future innovations. We believe that the knowledge and insights contained within these pages will empower readers to lead the way in creating innovative solutions that will shape the future of technology. Thank you for joining us on this journey. Authors
The Application Of Artificial Intelligence
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Author : Zoltán Somogyi
language : en
Publisher: Springer Nature
Release Date : 2021-03-11
The Application Of Artificial Intelligence written by Zoltán Somogyi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-11 with Computers categories.
This book presents a unique, understandable view of machine learning using many practical examples and access to free professional software and open source code. The user-friendly software can immediately be used to apply everything you learn in the book without the need for programming. After an introduction to machine learning and artificial intelligence, the chapters in Part II present deeper explanations of machine learning algorithms, performance evaluation of machine learning models, and how to consider data in machine learning environments. In Part III the author explains automatic speech recognition, and in Part IV biometrics recognition, face- and speaker-recognition. By Part V the author can then explain machine learning by example, he offers cases from real-world applications, problems, and techniques, such as anomaly detection and root cause analyses, business process improvement, detecting and predicting diseases, recommendation AI, several engineering applications, predictive maintenance, automatically classifying datasets, dimensionality reduction, and image recognition. Finally, in Part VI he offers a detailed explanation of the AI-TOOLKIT, software he developed that allows the reader to test and study the examples in the book and the application of machine learning in professional environments. The author introduces core machine learning concepts and supports these with practical examples of their use, so professionals will appreciate his approach and use the book for self-study. It will also be useful as a supplementary resource for advanced undergraduate and graduate courses on machine learning and artificial intelligence.
Ai Simplified Artificial Intelligence Made Simpler For Seniors
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Author : DIZZY DAVIDSON
language : en
Publisher: Pure Water Books
Release Date : 2025-04-12
Ai Simplified Artificial Intelligence Made Simpler For Seniors written by DIZZY DAVIDSON and has been published by Pure Water Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-12 with Family & Relationships categories.
AI Simplified: Artificial Intelligence Made Simple for Seniors If you've ever felt left behind in today's tech-driven world, or if you'd love to impress your grandkids with your newfound tech-savviness, then this book is for you! Whether you're curious about the smart gadgets around your house or just want to make the most of technology in your daily life, this beginner-friendly guide to artificial intelligence will empower you to embrace AI with confidence and ease. Packed with tips, tricks, and step-by-step guides, this book transforms complex AI concepts into simple, relatable lessons. Discover the magic of artificial intelligence through real-life stories, engaging illustrations, and examples that bring technology to life. This is your ultimate companion to unlocking the potential of AI—tailored specifically for seniors. Benefits of This Book: · Discover How AI Enhances Everyday Life: Learn how artificial intelligence powers tools you already use, like smartphones, smart home devices, and online shopping platforms. · Master AI-Powered Tools: Get step-by-step instructions for using video calls, voice assistants, and health tracking apps like a pro. · Stay Safe and Secure Online: Protect your personal information with AI tools that make online safety simple and stress-free. · Explore New Hobbies with AI: Use AI-powered creativity tools for writing, gardening tips, and learning new skills. · Boost Your Confidence: Gain a clear understanding of tech jargon and navigate technology without fear. This book isn’t just a guide—it’s a journey to staying connected, informed, and inspired in an ever-changing world. Join the growing community of seniors who are embracing technology and discovering its endless possibilities. Don’t wait to change your relationship with technology—get your copy today!
Foundations Of Artificial Intelligence And Machine Learning
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Author : Mr. Brajesh Kumar Sharma
language : en
Publisher: Chyren Publication
Release Date : 2025-06-30
Foundations Of Artificial Intelligence And Machine Learning written by Mr. Brajesh Kumar Sharma and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-30 with Antiques & Collectibles categories.