Troubleshooting Python Machine Learning
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Troubleshooting Python Machine Learning
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Author : Rudy Lai
language : en
Publisher:
Release Date : 2018
Troubleshooting Python Machine Learning written by Rudy Lai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
"Troubleshooting Python Machine Learning is the answer. We have systematically researched common ML problems documented online around data wrangling, debugging models such as Random Forests and SVMs, and visualizing tricky results. We leverage statistics from Stack Overflow, Medium, and GitHub to get a cross-section of what data scientists struggle with. We have collated for you the top issues, such as retrieving the most important regression features and explaining your results after clustering, and their corresponding solutions. We present these case studies in a problem-solution format, making it very easy for you to incorporate this into your knowledge. Taking this course will help you to precisely debug your models and research pipelines, so you can focus on pitching new ideas and not fixing old bugs."--Resource description page.
Practical Machine Learning With Python
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Author : Dipanjan Sarkar
language : en
Publisher: Apress
Release Date : 2017-12-20
Practical Machine Learning With Python written by Dipanjan Sarkar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-20 with Computers categories.
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 andframeworks 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
Python Machine Learning
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Author : Wei-Meng Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-30
Python Machine Learning written by Wei-Meng Lee 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 2019-04-30 with Computers categories.
Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart—it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand. Python data science—manipulating data and data visualization Data cleansing Understanding Machine learning algorithms Supervised learning algorithms Unsupervised learning algorithms Deploying machine learning models Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level.
Troubleshooting Python Deep Learning
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Author : Jakub Konczyk
language : en
Publisher:
Release Date : 2019
Troubleshooting Python Deep Learning written by Jakub Konczyk and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Practical solutions to your problems while building Deep Learning models using CNN, LSTM, scikit-learn, and NumPy About This Video Discover the limitless use of building any application using Deep Learning and ensure its issues aren't a roadblock for your projects Problems are addressed with practical yet unique solutions that are easy to understand and implement Implement scikit-learn and NumPy, to resolve the common problems arising from Deep Learning models In Detail Building Deep Learning models with Python is a strenuous task and there are chances of getting stuck on specific tasks. When that happens, you usually end up searching for solutions and need to manually look for ways to resolve these problems. This wastes both time and effort, and may also lead to reduced performance of your Deep Learning system. After carefully analyzing the most popular errors or problems that arise while working on Deep Learning models, we have identified the most usable models used for classification in this course and provided practical yet unique solutions to each problem that are easy to understand and implement. You can either follow the entire course or directly jump into the section that covers a specific problem you're facing. Some of the common yet important issues we cover include errors while building and training Deep Learning with neural networks, especially without a specific framework. By the end of the course, you will be well-versed to tackle and troubleshoot any errors with your Deep Learning models. Downloading the example code for this course: You can download the example code files for this course on GitHub at the following link: https://github.com/PacktPublishing/Troubleshooting-Python-Deep-Learning . If you require support please email: [email protected].
Combating Women S Health Issues With Machine Learning
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Author : D. Hemanth
language : en
Publisher: CRC Press
Release Date : 2023-10-23
Combating Women S Health Issues With Machine Learning written by D. Hemanth and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-23 with Medical categories.
The main focus of this book is the examination of women’s health issues and the role machine learning can play as a solution to these challenges. This book will illustrate advanced, innovative techniques/frameworks/concepts/machine learning methodologies, enhancing the future healthcare system. Combating Women’s Health Issues with Machine Learning: Challenges and Solutions examines the fundamental concepts and analysis of machine learning algorithms. The editors and authors of this book examine new approaches for different age-related medical issues that women face. Topics range from diagnosing diseases such as breast and ovarian cancer to using deep learning in prenatal ultrasound diagnosis. The authors also examine the best machine learning classifier for constructing the most accurate predictive model for women’s infertility risk. Among the topics discussed are gender differences in type 2 diabetes care and its management as it relates to gender using artificial intelligence. The book also discusses advanced techniques for evaluating and managing cardiovascular disease symptoms, which are more common in women but often overlooked or misdiagnosed by many healthcare providers. The book concludes by presenting future considerations and challenges in the field of women’s health using artificial intelligence. This book is intended for medical researchers, healthcare technicians, scientists, programmers and graduate-level students looking to understand better and develop applications of machine learning/deep learning in healthcare scenarios, especially concerning women’s health conditions.
Challenging Programming In Python A Problem Solving Perspective
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Author : Habib Izadkhah
language : en
Publisher: Springer Nature
Release Date : 2023-10-17
Challenging Programming In Python A Problem Solving Perspective written by Habib Izadkhah and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-17 with Technology & Engineering categories.
This book aims to strengthen programming skills and foster creative thinking by presenting and solving 90 challenging problems. The book is intended for individuals with elementary, intermediate, and advanced Python programming skills who aspire to take their abilities to the next level. Additionally, the book is valuable for individuals interested in enhancing their creative thinking and logical reasoning skills. It is a self-instructional book meant to provide readers with the ability to solve challenging problems independently. The presented challenges are lucidly and succinctly expressed, facilitating readers to follow along and comprehend the problem-solving process. The challenges cover various fields, making it suitable for a wide range of individuals. The book is divided into eight chapters, beginning with an introduction in chapter one. The second chapter presents essential Python basics for programming challenging problems, while the subsequent chapters focus on specific types of challenges. These include math-based challenges in chapter three, number-based challenges in chapter four, string-based challenges in chapter five, game-based challenges in chapter six, count-based challenges in chapter seven, and miscellaneous challenges in chapter eight. Each chapter comprises a set of challenges with examples, hints, algorithms, and Python code solutions. The target audience of the book includes computer science and engineering students, teachers, software developers, and participants in programming competitions.
Python Machine Learning For Beginners
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Author : Finn Sanders
language : en
Publisher: Roland Bind
Release Date : 2019-05-22
Python Machine Learning For Beginners written by Finn Sanders and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-22 with Computers categories.
Imagine a world where you can make a computer program learn for itself? What if it could recognize who is in a picture or the exact websites that you want to look for when you type it into the program? What if you were able to create any kind of program that you wanted, even as a beginner programmer, without all of the convoluted codes and other information that makes your head spin? This is actually all possible. The programs that were mentioned before are all a part of machine learning. This is a breakthrough in the world of information technology, which allows the computer to learn how to behave, rather than asking the programmer to think of every single instance that may show up with their user ahead of time. it is taking over the world, and you may be using it now, without even realizing it. If you have used a search engine, worked with photo recognition, or done speech recognition devices on your phone, then you have worked with machine learning. And if you combine it with the Python programming language, it is faster, more powerful, and easier (even for beginners) to create your own programs today. Python is considered the ultimate coding language for beginners, but once you start to use it, you will never be able to tell. Many of the best programs out there use this language behind them, and if you are a beginner who is ready to learn, this is a great place to start. If you have a program in mind, or you just want to be able to get some programming knowledge and learn more about the power that comes behind it, then this is the guidebook for you. ★★Some of the topics that we will discuss include★★ ♦ The Fundamentals of Machine Learning, Deep learning, And Neural Networks ♦ How To Set Up Your Environment And Make Sure That Python, TensorFlow And Scikit-Learn Work Well For You ♦ How To Master Neural Network Implementation Using Different Libraries ♦ How Random Forest Algorithms Are Able To Help Out With Machine Learning ♦ How To Uncover Hidden Patterns And Structures With Clustering ♦ How Recurrent Neural Networks Work And When To Use ♦ The Importance Of Linear Classifiers And Why They Need To Be Used In Machine Learning ♦ And Much More! This guidebook is going to provide you with the information you need to get started with Python Machine Learning. If you have an idea for a great program, but you don't have the technical knowledge to make it happen, then this guidebook will help you get started. Machine learning has the capabilities, and Python has the ease, to help you, even as a beginner, create any product that you would like. If you want to learn more about how to make the best programs with Python Machine learning, buy the book today!
Kickstart Python Programming Fundamentals
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Author : Jit Sinha
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-06-24
Kickstart Python Programming Fundamentals written by Jit Sinha and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-24 with Computers categories.
TAGLINE Keep Calm and Let Us Tame the Python. KEY FEATURES ● Beginner-friendly with clear examples and no prior coding needed. ● Step-by-step projects from basics to real-world applications. ● Hands-on learning with flowcharts, functions, and data tools. DESCRIPTION Python is more than a programming language—it’s a career catalyst. Whether you're aiming to future-proof your skills, automate everyday tasks, or break into tech, Python is the gateway. Kickstart Python Programming Fundamentals is your launchpad, built specifically for absolute beginners, freshers, students, and professionals with no coding background. With crystal-clear explanations, real-world examples, and zero jargon, this book makes programming accessible, engaging, and fun. You’ll start by writing your first Python program and gradually master essential concepts like variables, loops, functions, and data structures. From there, you'll progress to object-oriented programming, file handling, working with databases, and even get a taste of AI and data analysis. Each chapter includes hands-on exercises and mini-projects to solidify your learning. By the end, you'll not only understand Python—you’ll be building real-world solutions, building a project portfolio, and ready to take on academic, personal, or professional challenges. The future is coded—start your journey today and don’t get left behind. WHAT WILL YOU LEARN ● Write and run your first Python programs with confidence. ● Understand and use variables, data types, and Python syntax. ● Build logic-driven programs using loops and conditionals. ● Create clean, reusable code with functions and parameters. ● Organize and manipulate data using lists, dictionaries, tuples, and sets. ● Read and write files, handle errors, and explore basic AI concepts. ● Apply your skills in real-world projects and coding challenges. WHO IS THIS BOOK FOR? This book is for absolute beginners, including students, fresh graduates, hobbyists, career switchers, and professionals from non-technical backgrounds. Whether you're a complete novice, a fresher with no coding experience, or simply curious about programming, this book offers a clear, hands-on path to start your journey with Python—no prior knowledge required. TABLE OF CONTENTS 1. Beginning with Python 2. Introduction to Algorithms and Flowcharts 3. Basic Python 4. Making Choices and Repeating Actions 5. Creating Functions 6. Organizing Data 7. Understanding OOP in Python 8. Using Modules and Packages 9. Error Handling 10. File Handling and String Manipulation 11. Dates and Times 12. Working with JSON and XML 13. Math in Python 14. Managing Packages with PIP 15. Building Web Apps 16. Python and Databases 17. Analyzing Data 18. Python in Artificial Intelligence 19. Conclusion and Next Steps 20. Real-World Project Index
Methodologies Frameworks And Applications Of Machine Learning
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Author : Srivastava, Pramod Kumar
language : en
Publisher: IGI Global
Release Date : 2024-03-22
Methodologies Frameworks And Applications Of Machine Learning written by Srivastava, Pramod Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-22 with Computers categories.
Technology is constantly evolving, and machine learning is positioned to become a pivotal tool with the power to transform industries and revolutionize everyday life. This book underscores the urgency of leveraging the latest machine learning methodologies and theoretical advancements, all while harnessing a wealth of realistic data and affordable computational resources. Machine learning is no longer confined to theoretical domains; it is now a vital component in healthcare, manufacturing, education, finance, law enforcement, and marketing, ushering in an era of data-driven decision-making. Academic scholars seeking to unlock the potential of machine learning in the context of Industry 5.0 and advanced IoT applications will find that the groundbreaking book, Methodologies, Frameworks, and Applications of Machine Learning, introduces an unmissable opportunity to delve into the forefront of modern research and application. This book offers a wealth of knowledge and practical insights across a wide array of topics, ranging from conceptual frameworks and methodological approaches to the application of probability theory, statistical techniques, and machine learning in domains as diverse as e-government, healthcare, cyber-physical systems, and sustainable development, this comprehensive guide equips you with the tools to navigate the complexities of Industry 5.0 and the Internet of Things (IoT).
International Scientific Applied Conference Problems Of Emergency Situations Pes
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Author : Alexey Vasilchenko
language : en
Publisher: Trans Tech Publications Ltd
Release Date : 2025-12-19
International Scientific Applied Conference Problems Of Emergency Situations Pes written by Alexey Vasilchenko and has been published by Trans Tech Publications Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-19 with Technology & Engineering categories.
Selected peer-reviewed extended articles based on abstracts presented at the International Scientific Applied Conference "Problems of Emergency Situations" (PES 2025) Aggregated Book