Machine Learning Essentials
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Machine Learning Essentials And Applications
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Author : Mrs. N. Jayasri
language : en
Publisher: RK Publication
Release Date : 2024-07-27
Machine Learning Essentials And Applications written by Mrs. N. Jayasri and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-27 with Computers categories.
Machine Learning Essentials and Applications a comprehensive of machine learning's core principles, methodologies, and real-world applications. This book is designed for both beginners and professionals, covering essential topics like supervised and unsupervised learning, neural networks, and deep learning. With clear explanations and practical examples, it connects theory to practice, showcasing machine learning’s impact across industries such as healthcare, finance, and technology. Ideal for readers seeking foundational knowledge and insights into the transformative potential of machine learning in various fields.
Machine Learning Essentials You Always Wanted To Know
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Author : Dhairya Parikh
language : en
Publisher: Vibrant Publishers
Release Date : 2025-07-04
Machine Learning Essentials You Always Wanted To Know written by Dhairya Parikh and has been published by Vibrant Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Business & Economics categories.
· Covers key algorithms and techniques · Ideal for students and professionals · Hands-on implementation included Master the fundamentals of ML and take the first step towards a career in AI! In today’s rapidly evolving world, machine learning (ML) is no longer just for researchers or data scientists. From personalized recommendations on streaming platforms to fraud detection in banking, ML powers many aspects of our daily lives. As industries increasingly adopt AI-driven solutions, learning machine learning has become a valuable skill. Yet, many find the subject overwhelming, often intimidated by its mathematical complexity. That’s where Machine Learning Essentials You Always Wanted to Know (Machine Learning Essentials) comes in. This beginner-friendly guide offers a structured, step-by-step approach to understanding machine learning concepts without unnecessary jargon. Whether you are a student, a professional looking to transition into AI, or simply curious about how machines learn, this book provides a clear and practical roadmap to mastering ML. Authored by Dhairya Parikh, an experienced data engineer who returned to academia to refine his expertise, this book bridges the gap between theory and real-world application. It simplifies the core concepts of ML, breaking them down into digestible explanations paired with hands-on coding exercises to help you apply what you learn. What You’ll Learn: · The fundamentals of machine learning and how it powers modern technology · The three key types of ML—Supervised, Unsupervised, and Reinforcement Learning · How to combine algorithms, data, and models to develop AI-driven solutions · Practical coding techniques to build and implement machine learning models Part of Vibrant Publishers’ Self-Learning Management Series, this book serves as a valuable guide for building machine learning skills, enhancing your expertise, and advancing your career in AI and data science.
Machine Learning Essentials
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Author : Alboukadel Kassambara
language : en
Publisher: STHDA
Release Date : 2018-03-10
Machine Learning Essentials written by Alboukadel Kassambara and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-10 with Computers categories.
Discovering knowledge from big multivariate data, recorded every days, requires specialized machine learning techniques. This book presents an easy to use practical guide in R to compute the most popular machine learning methods for exploring real word data sets, as well as, for building predictive models. The main parts of the book include: A) Unsupervised learning methods, to explore and discover knowledge from a large multivariate data set using clustering and principal component methods. You will learn hierarchical clustering, k-means, principal component analysis and correspondence analysis methods. B) Regression analysis, to predict a quantitative outcome value using linear regression and non-linear regression strategies. C) Classification techniques, to predict a qualitative outcome value using logistic regression, discriminant analysis, naive bayes classifier and support vector machines. D) Advanced machine learning methods, to build robust regression and classification models using k-nearest neighbors methods, decision tree models, ensemble methods (bagging, random forest and boosting). E) Model selection methods, to select automatically the best combination of predictor variables for building an optimal predictive model. These include, best subsets selection methods, stepwise regression and penalized regression (ridge, lasso and elastic net regression models). We also present principal component-based regression methods, which are useful when the data contain multiple correlated predictor variables. F) Model validation and evaluation techniques for measuring the performance of a predictive model. G) Model diagnostics for detecting and fixing a potential problems in a predictive model. The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers. Key features: - Covers machine learning algorithm and implementation - Key mathematical concepts are presented - Short, self-contained chapters with practical examples.
Machine Learning Essentials A Practical Guide To Building Accurate And Reliable Models
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Author : Devansh Dhiman
language : en
Publisher: Devansh Dhiman
Release Date : 2023-05-01
Machine Learning Essentials A Practical Guide To Building Accurate And Reliable Models written by Devansh Dhiman and has been published by Devansh Dhiman this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-01 with Business & Economics categories.
Machine learning is a powerful tool for making accurate predictions and improving decision-making based on data-driven insights. However, building accurate and reliable machine learning models requires a thorough understanding of the machine learning workflow, from data preprocessing and exploration to model training and deployment. In this ebook, we provide a practical guide to machine learning essentials, covering everything from the basics of supervised and unsupervised learning to deep learning and model deployment. We explore common machine learning algorithms, including decision trees, support vector machines, and neural networks, and provide examples of how they can be used in real-world applications. We also delve into data preprocessing and exploration, discussing techniques for cleaning, transforming, and scaling data to make it suitable for analysis, and exploring ways to gain insights into the properties and relationships of the data. We discuss best practices for model training and evaluation, and explore strategies for deploying and maintaining machine learning models in a production environment. Whether you're an experienced data scientist or just starting out, this ebook provides a comprehensive guide to building accurate and reliable machine learning models that can transform your business and improve decision-making based on data-driven insights.
R Machine Learning Essentials
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Author : Michele Usuelli
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-11-28
R Machine Learning Essentials written by Michele Usuelli 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 2014-11-28 with Computers categories.
If you want to learn how to develop effective machine learning solutions to your business problems in R, this book is for you. It would be helpful to have a bit of familiarity with basic object-oriented programming concepts, but no prior experience is required.
R Deep Learning Essentials
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Author : Mark Hodnett
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-24
R Deep Learning Essentials written by Mark Hodnett 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 2018-08-24 with Computers categories.
Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a range of datasets Book Description Deep learning is a powerful subset of machine learning that is very successful in domains such as computer vision and natural language processing (NLP). This second edition of R Deep Learning Essentials will open the gates for you to enter the world of neural networks by building powerful deep learning models using the R ecosystem. This book will introduce you to the basic principles of deep learning and teach you to build a neural network model from scratch. As you make your way through the book, you will explore deep learning libraries, such as Keras, MXNet, and TensorFlow, and create interesting deep learning models for a variety of tasks and problems, including structured data, computer vision, text data, anomaly detection, and recommendation systems. You’ll cover advanced topics, such as generative adversarial networks (GANs), transfer learning, and large-scale deep learning in the cloud. In the concluding chapters, you will learn about the theoretical concepts of deep learning projects, such as model optimization, overfitting, and data augmentation, together with other advanced topics. By the end of this book, you will be fully prepared and able to implement deep learning concepts in your research work or projects. What you will learn Build shallow neural network prediction models Prevent models from overfitting the data to improve generalizability Explore techniques for finding the best hyperparameters for deep learning models Create NLP models using Keras and TensorFlow in R Use deep learning for computer vision tasks Implement deep learning tasks, such as NLP, recommendation systems, and autoencoders Who this book is for This second edition of R Deep Learning Essentials is for aspiring data scientists, data analysts, machine learning developers, and deep learning enthusiasts who are well versed in machine learning concepts and are looking to explore the deep learning paradigm using R. Fundamental understanding of the R language is necessary to get the most out of this book.
Machine Learning Essentials
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Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2024-12-01
Machine Learning Essentials written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-01 with Computers categories.
Unlock the potential of data and step into the future with "Machine Learning Essentials," the ultimate guide for mastering predictive analytics. Whether you're a newcomer or looking to deepen your understanding, this comprehensive eBook is designed to equip you with the tools and knowledge you need to excel in the dynamic field of machine learning. Begin your journey by exploring the foundational principles of machine learning and its transformative impact on predictive analytics. Learn how to expertly prepare and engineer your data, selecting and extracting the features that matter most. Dive into handling imbalanced data with precision, ensuring your models are accurate and robust. Discover the power of classification algorithms with insights into decision trees, random forests, support vector machines, and logistic regression. Transition smoothly into regression techniques, harnessing the potential of linear, polynomial, and regularization methods. Explore the realm of unsupervised learning to unveil predictive insights using clustering methods, dimensionality reduction techniques, and anomaly detection. Evaluate model performance like a pro with cross-validation strategies, confusion matrices, and ROC/AUC metrics. Venture into neural networks, unlocking the basics of their architecture, activation functions, and training methodologies. Delve into advanced deep learning topics with convolutional, recurrent, and generative adversarial networks. Optimize your models through hyperparameter tuning and feature importance analysis, selecting the most effective techniques for your goals. Gain practical business insights by implementing machine learning in marketing analytics, risk assessment, and fraud detection. Familiarize yourself with essential tools and libraries like Python, Scikit-Learn, TensorFlow, and PyTorch. Learn from real-world case studies in retail, healthcare, and finance, and tackle ethical considerations in algorithmic bias and data security. Prepare for the future with insights into automated machine learning, IoT, and evolving AI technologies. Take practical steps to launch your machine learning journey, setting up your environment and connecting with a vibrant community of practitioners. "Machine Learning Essentials" is your all-in-one resource for gaining actionable expertise and driving innovation in today's data-driven world. Start your learning adventure today and transform your career with this indispensable guide.
Machine Learning 101
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Author : William Owen Ph D
language : en
Publisher:
Release Date : 2021-05-18
Machine Learning 101 written by William Owen Ph D and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-18 with categories.
Althоugh machine lеаrnіng іѕ a fіеld within соmрutеr ѕсіеnсе, it dіffеrѕ frоm traditional соmрutаtіоnаl approaches. In traditional соmрutіng, algorithms аrе ѕеtѕ оf еxрlісіtlу programmed instructions used by computers tо саlсulаtе оr рrоblеm ѕоlvе Mасhіnе lеаrnіng іѕ a ѕubfіеld оf artificial intelligence (AI). The goal оf machine learning generally іѕ tо understand thе ѕtruсturе оf data аnd fit thаt dаtа іntо mоdеlѕ thаt саn be understood аnd utіlіzеd by реорlе.
Python Machine Learning Essentials
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Author : Bernard Baah
language : en
Publisher: Independently Published
Release Date : 2024-03-22
Python Machine Learning Essentials written by Bernard Baah and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.
"Python Machine Learning Essentials" by Bernard Baah is your ultimate guide to mastering machine learning concepts and techniques using Python. Whether you're a beginner or an experienced programmer, this book equips you with the knowledge and skills needed to understand and apply machine learning algorithms effectively. With a comprehensive approach, Bernard Baah takes you through the fundamentals of machine learning, covering Python basics, data preprocessing, exploratory data analysis, supervised and unsupervised learning, neural networks, natural language processing, model deployment, and more. Each chapter is filled with practical examples, code snippets, and hands-on exercises to reinforce your learning and deepen your understanding. As the founder of Filly Coder (https: //fillycoder.com), Bernard Baah brings years of experience in machine learning and software development to this book. His expertise and passion for teaching shine through, making complex concepts accessible and understandable for readers of all levels. Whether you're a data scientist, developer, or aspiring AI enthusiast, "Python Machine Learning Essentials" is your go-to resource for mastering machine learning with Python. Dive into the world of machine learning and unlock the potential to build intelligent applications with confidence. Get your copy of "Python Machine Learning Essentials" today and embark on your journey to becoming a proficient machine learning practitioner
R Machine Learning Essentials
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Author : Michele Usuelli
language : en
Publisher:
Release Date : 2014-11-28
R Machine Learning Essentials written by Michele Usuelli and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-28 with Computers categories.
If you want to learn how to develop effective machine learning solutions to your business problems in R, this book is for you. It would be helpful to have a bit of familiarity with basic object-oriented programming concepts, but no prior experience is required.