Machine Learning With Lightgbm And Python
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Machine Learning With Lightgbm And Python
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Author : Andrich van Wyk
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-09-29
Machine Learning With Lightgbm And Python written by Andrich van Wyk 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 2023-09-29 with Computers categories.
Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and Python Key Features Get started with LightGBM, a powerful gradient-boosting library for building ML solutions Apply data science processes to real-world problems through case studies Elevate your software by building machine learning solutions on scalable platforms Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release. This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI. By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learn Get an overview of ML and working with data and models in Python using scikit-learn Explore decision trees, ensemble learning, gradient boosting, DART, and GOSS Master LightGBM and apply it to classification and regression problems Tune and train your models using AutoML with FLAML and Optuna Build ML pipelines in Python to train and deploy models with secure and performant APIs Scale your solutions to production readiness with AWS Sagemaker, PostgresML, and Dask Who this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book. The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.
Practical Machine Learning With Lightgbm And Python
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Author : ROSHAN. BHAVE
language : en
Publisher:
Release Date : 2021-08
Practical Machine Learning With Lightgbm And Python written by ROSHAN. BHAVE and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08 with Machine learning categories.
Scikit Learn Xgboost And Lightgbm For Beginners
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Author : Haider Koele
language : en
Publisher: Independently Published
Release Date : 2025-09-04
Scikit Learn Xgboost And Lightgbm For Beginners written by Haider Koele and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-04 with Computers categories.
Unlock the World of Machine Learning-No Experience Required! Do you feel overwhelmed by complex jargon and endless lines of code every time you think about learning machine learning? Have you wondered if you're "tech-savvy enough" to break into AI, or wished for a resource that makes the journey friendly, practical, and genuinely enjoyable? This is the beginner's book you've been searching for. Inside Scikit-Learn, XGBoost, and LightGBM for Beginners, you'll discover a warm, step-by-step guide that demystifies machine learning from the ground up-designed especially for readers with no prior experience. You don't need a computer science degree, advanced math skills, or a background in programming. All you need is curiosity, patience, and the desire to learn by doing. What Makes This Book Different? Gentle, Encouraging Approach: Every chapter is crafted to nurture your confidence and curiosity. Mistakes are normalized, progress is celebrated, and learning feels like an adventure-not a test. Step-by-Step Learning: Follow clear explanations and practical examples, from your very first line of Python code to building real machine learning projects with Scikit-Learn, XGBoost, and LightGBM. Hands-On Projects: Apply what you learn to real-world datasets and scenarios, so you gain skills that are both practical and relevant. Modern, In-Demand Tools: Master three of today's most popular frameworks-Scikit-Learn for accessible machine learning, XGBoost for powerful performance, and LightGBM for cutting-edge speed. No Experience Needed: Written with absolute beginners in mind, with jargon gently explained, plenty of support, and troubleshooting tips at every step. Complete Learning Journey: From setting up your environment, cleaning data, and building models to interpreting results and deploying solutions-you'll walk away with genuine confidence and tangible skills. Key Takeaways: Learn Python-based machine learning in plain language, with zero prior coding required Build, evaluate, and deploy real models using Scikit-Learn, XGBoost, and LightGBM Tackle practical projects that make your learning stick-classification, regression, pipelines, and more Overcome imposter syndrome with a nurturing, supportive tone that makes mistakes part of the process Prepare for real-world jobs, data science interviews, or personal projects with in-demand, industry-tested tools Find your place in the machine learning community-regardless of your background or experience Start Your Machine Learning Journey with Confidence! Whether your dream is to build smarter apps, break into data science, or simply understand the technology shaping our world, this book will guide you every step of the way. Embrace a hands-on, beginner-friendly approach that makes learning machine learning achievable, enjoyable, and even fun. Ready to transform confusion into confidence? Open this book, take your first step, and let your machine learning adventure begin!
Hands On Gradient Boosting With Python
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Author : Dr Adrian Devlin
language : en
Publisher: Independently Published
Release Date : 2025-12-11
Hands On Gradient Boosting With Python written by Dr Adrian Devlin and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-11 with Computers categories.
Are you curious about machine learning but feel overwhelmed by math, jargon, and complex tutorials? If words like XGBoost, LightGBM, and gradient boosting sound exciting but intimidating, this book is your friendly guide through the noise. Hands-On Gradient Boosting with Python: A Practical Introduction to XGBoost, LightGBM, and the Scikit-Learn Ecosystem is written for complete beginners and self-taught developers who want a clear, step-by-step path into modern Python machine learning-without needing a PhD or years of coding experience. You'll start with the basics of Python, scikit-learn, and tabular data, then gently build up to powerful boosting models used in real-world projects and Kaggle competitions. Every chapter walks you through code line by line, explains why each step matters, and shows you how to avoid common mistakes. Inside, you'll learn how to: Set up your Python machine learning environment with confidence Understand core concepts like decision trees, ensembles, and gradient boosting in plain English Build practical models with scikit-learn, XGBoost, and LightGBM for regression and classification Work on real-world projects such as house price prediction and credit risk scoring Tune hyperparameters, handle imbalanced data, and evaluate models with metrics like AUC, F1, and RMSE Use SHAP and LIME for model explainability so you can trust your predictions Save, load, and deploy your models so they are ready for real applications Throughout the book, you're treated like a learner-not a walking error message. Mistakes are normalized, experiments are encouraged, and every "small win" is celebrated: Clear explanations before any code Gradual progression from simple to advanced models Gentle reminders that confusion is part of learning Practical tips for debugging, improving, and reusing your work Whether you're a student, an aspiring data scientist, or a developer stepping into Python machine learning for the first time, this book becomes your supportive companion-one that makes gradient boosting feel approachable, understandable, and genuinely fun. If you're ready to stop scrolling tutorials and start building real models that actually work, open this book and begin your hands-on journey into gradient boosting with Python today.
Artificial Intelligence For Managers
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Author : Rakesh Dandu
language : en
Publisher: Notion Press
Release Date : 2020-05-27
Artificial Intelligence For Managers written by Rakesh Dandu and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-27 with Computers categories.
This book is for business leaders, product managers, HR managers, non-engineers, principals, academicians and students This book is for you if: You are a manager at any level or working in any field such as human resource, product management, customer service, business management, sales, finance, CXO, school principal, head of departments, from art and entertainment or any individual with an enthusiasm for technology who wishes to understand how AI works, its various components, AI life cycle, and its real-life implementation. You wish to know how AI can benefit your current job and organization. You want to upgrade your knowledge on AI without having to learn all the technical details.
Machine Learning For Civil And Environmental Engineers
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Author : M. Z. Naser
language : en
Publisher: John Wiley & Sons
Release Date : 2023-08-08
Machine Learning For Civil And Environmental Engineers written by M. Z. Naser and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-08 with Technology & Engineering categories.
Accessible and practical framework for machine learning applications and solutions for civil and environmental engineers This textbook introduces engineers and engineering students to the applications of artificial intelligence (AI), machine learning (ML), and machine intelligence (MI) in relation to civil and environmental engineering projects and problems, presenting state-of-the-art methodologies and techniques to develop and implement algorithms in the engineering domain. Through real-world projects like analysis and design of structural members, optimizing concrete mixtures for site applications, examining concrete cracking via computer vision, evaluating the response of bridges to hazards, and predicating water quality and energy expenditure in buildings, this textbook offers readers in-depth case studies with solved problems that are commonly faced by civil and environmental engineers. The approaches presented range from simplified to advanced methods, incorporating coding-based and coding-free techniques. Professional engineers and engineering students will find value in the step-by-step examples that are accompanied by sample databases and codes for readers to practice with. Written by a highly qualified professional with significant experience in the field, Machine Learning includes valuable information on: The current state of machine learning and causality in civil and environmental engineering as viewed through a scientometrics analysis, plus a historical perspective Supervised vs. unsupervised learning for regression, classification, and clustering problems Explainable and causal methods for practical engineering problems Database development, outlining how an engineer can effectively collect and verify appropriate data to be used in machine intelligence analysis A framework for machine learning adoption and application, covering key questions commonly faced by practitioners This textbook is a must-have reference for undergraduate/graduate students to learn concepts on the use of machine learning, for scientists/researchers to learn how to integrate machine learning into civil and environmental engineering, and for design/engineering professionals as a reference guide for undertaking MI design, simulation, and optimization for infrastructure.
Nutrition And Metabolism In Kidney Diseases
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Author : Cassiana Regina Goes
language : en
Publisher: Frontiers Media SA
Release Date : 2023-03-09
Nutrition And Metabolism In Kidney Diseases written by Cassiana Regina Goes and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-09 with Medical categories.
Artificial Intelligence For Energy Systems
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Author : Elissaios Sarmas
language : en
Publisher: Springer Nature
Release Date : 2025-03-21
Artificial Intelligence For Energy Systems written by Elissaios Sarmas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-21 with Computers categories.
This book focuses on creating an integrated library of learning models and optimization techniques to assist decision-making on issues in the energy and building sector. It provides modern solutions to energy management and efficiency while addressing a scientific gap in the development of advanced algorithmic methods to solve these problems. More specifically, the focus is on the development of models and algorithms for problems falling into three broader categories, namely: (a) Distributed Energy Generation, (b) Microgrid Flexibility, and (c) Building Energy Efficiency. Artificial Intelligence models and mathematical optimization techniques are developed and presented for applications related to each of these categories, through a thorough analysis of the fundamental parameters of each application as well as the interactions among them. Professors, researchers, scientists, engineers, and students in energy sector-related disciplines are expected to be inspired and benefit from this book, along with readers from other disciplines wishing to learn more about this exciting new field of research.
Proceedings Of The International Health Informatics Conference
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Author : Sarika Jain
language : en
Publisher: Springer Nature
Release Date : 2025-03-05
Proceedings Of The International Health Informatics Conference written by Sarika Jain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-05 with Medical categories.
This book will constitute the proceedings of the International Health Informatics Conference (IHIC 2023). This volume focus on artificial intelligence, machine learning, and deep learning approach with their automated intelligent cognitive knowledge as an assisting tool to the existing healthcare tools. The topics covered in this volume are data mining, patient electronic health records, healthcare portals, telemedicine, automatic identification and data collector systems, RFID and localization techniques, usability and ubiquity in e-Health, artificial intelligence for healthcare decision-making, etc. This volume will prove a valuable resource for those in academia and industry.
Hands On Machine Learning Techniques
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Author : Dr Benjamin Neudorf
language : en
Publisher: Independently Published
Release Date : 2025-08-24
Hands On Machine Learning Techniques written by Dr Benjamin Neudorf and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-24 with Computers categories.
Are you curious about machine learning but feel overwhelmed by technical jargon or afraid to take the first step? You're not alone-and you're exactly who this book was written for. Hands-On Machine Learning Techniques: Scikit-Learn, XGBoost, and LightGBM for Beginners to Advanced is your friendly, step-by-step guide to unlocking the power of data science-no prior experience or advanced math required. Whether you're a complete beginner, an aspiring data scientist, or a developer eager to master modern ML tools, this book will nurture your confidence, celebrate your progress, and empower you to create real-world solutions. What makes this book different? Welcoming, Encouraging Style: Written as a supportive companion, each chapter guides you gently through new concepts-explaining not just the "how," but the "why"-so you always feel included and understood. No Experience Needed: Start from scratch with Python, then grow into advanced machine learning using industry-standard libraries like Scikit-Learn, XGBoost, and LightGBM-all explained in clear, accessible language. Practical, Hands-On Learning: Build real projects, tackle messy data, and solve meaningful problems from the very first chapter. Mistakes are expected and embraced as part of your learning journey. Step-by-Step Examples: Follow concise, up-to-date code samples and workflows you can adapt to your own datasets, with helpful commentary to guide you at every turn. Confidence at Every Level: Move at your own pace through beginner basics, intermediate best practices, and advanced topics like model explainability, deployment, and real-world case studies. Expert Insights and Encouragement: Personal stories and honest advice help you navigate challenges, overcome self-doubt, and build the confidence to keep going-even when technology feels intimidating. Inside, you'll discover: The essential building blocks of machine learning with Python How to prepare, clean, and understand real-world data Powerful modeling techniques using Scikit-Learn, XGBoost, and LightGBM Practical guidance for data preprocessing, feature engineering, and hyperparameter tuning Strategies for interpreting models, addressing bias, and making results explainable How to build complete, end-to-end machine learning pipelines ready for production Deployment tips-share your models with the world using web apps and cloud services Inspiring real-world projects in finance, healthcare, and e-commerce Resources, checklists, and a troubleshooting guide for ongoing support Every chapter is designed to help you succeed-normalizing mistakes, celebrating small wins, and building momentum with each lesson. If you've ever felt left behind or anxious about learning machine learning, this book will be your steady guide. With warmth, clarity, and encouragement, you'll gain not just technical skills but the confidence to use them. Start your hands-on machine learning journey today. Let this book be your companion as you transform curiosity into real-world expertise-one approachable step at a time.