Hyperparameter Tuning With Python
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Hyperparameter Tuning With Python
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Author : Louis Owen
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29
Hyperparameter Tuning With Python written by Louis Owen 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 2022-07-29 with Computers categories.
Take your machine learning models to the next level by learning how to leverage hyperparameter tuning, allowing you to control the model's finest details Key Features • Gain a deep understanding of how hyperparameter tuning works • Explore exhaustive search, heuristic search, and Bayesian and multi-fidelity optimization methods • Learn which method should be used to solve a specific situation or problem Book Description Hyperparameters are an important element in building useful machine learning models. This book curates numerous hyperparameter tuning methods for Python, one of the most popular coding languages for machine learning. Alongside in-depth explanations of how each method works, you will use a decision map that can help you identify the best tuning method for your requirements. You'll start with an introduction to hyperparameter tuning and understand why it's important. Next, you'll learn the best methods for hyperparameter tuning for a variety of use cases and specific algorithm types. This book will not only cover the usual grid or random search but also other powerful underdog methods. Individual chapters are also dedicated to the three main groups of hyperparameter tuning methods: exhaustive search, heuristic search, Bayesian optimization, and multi-fidelity optimization. Later, you will learn about top frameworks like Scikit, Hyperopt, Optuna, NNI, and DEAP to implement hyperparameter tuning. Finally, you will cover hyperparameters of popular algorithms and best practices that will help you efficiently tune your hyperparameter. By the end of this book, you will have the skills you need to take full control over your machine learning models and get the best models for the best results. What you will learn • Discover hyperparameter space and types of hyperparameter distributions • Explore manual, grid, and random search, and the pros and cons of each • Understand powerful underdog methods along with best practices • Explore the hyperparameters of popular algorithms • Discover how to tune hyperparameters in different frameworks and libraries • Deep dive into top frameworks such as Scikit, Hyperopt, Optuna, NNI, and DEAP • Get to grips with best practices that you can apply to your machine learning models right away Who this book is for This book is for data scientists and ML engineers who are working with Python and want to further boost their ML model's performance by using the appropriate hyperparameter tuning method. Although a basic understanding of machine learning and how to code in Python is needed, no prior knowledge of hyperparameter tuning in Python is required.
Hyperparameter Tuning For Machine And Deep Learning With R
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Author : Eva Bartz
language : en
Publisher: Springer Nature
Release Date : 2023-01-01
Hyperparameter Tuning For Machine And Deep Learning With R written by Eva Bartz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-01 with Computers categories.
This open access book provides a wealth of hands-on examples that illustrate how hyperparameter tuning can be applied in practice and gives deep insights into the working mechanisms of machine learning (ML) and deep learning (DL) methods. The aim of the book is to equip readers with the ability to achieve better results with significantly less time, costs, effort and resources using the methods described here. The case studies presented in this book can be run on a regular desktop or notebook computer. No high-performance computing facilities are required. The idea for the book originated in a study conducted by Bartz & Bartz GmbH for the Federal Statistical Office of Germany (Destatis). Building on that study, the book is addressed to practitioners in industry as well as researchers, teachers and students in academia. The content focuses on the hyperparameter tuning of ML and DL algorithms, and is divided into two main parts: theory (Part I) and application (Part II). Essential topics covered include: a survey of important model parameters; four parameter tuning studies and one extensive global parameter tuning study; statistical analysis of the performance of ML and DL methods based on severity; and a new, consensus-ranking-based way to aggregate and analyze results from multiple algorithms. The book presents analyses of more than 30 hyperparameters from six relevant ML and DL methods, and provides source code so that users can reproduce the results. Accordingly, it serves as a handbook and textbook alike.
Practical Data Science With Python
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Author : Nathan George
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-30
Practical Data Science With Python written by Nathan George 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 2021-09-30 with Computers categories.
Learn to effectively manage data and execute data science projects from start to finish using Python Key FeaturesUnderstand and utilize data science tools in Python, such as specialized machine learning algorithms and statistical modelingBuild a strong data science foundation with the best data science tools available in PythonAdd value to yourself, your organization, and society by extracting actionable insights from raw dataBook Description Practical Data Science with Python teaches you core data science concepts, with real-world and realistic examples, and strengthens your grip on the basic as well as advanced principles of data preparation and storage, statistics, probability theory, machine learning, and Python programming, helping you build a solid foundation to gain proficiency in data science. The book starts with an overview of basic Python skills and then introduces foundational data science techniques, followed by a thorough explanation of the Python code needed to execute the techniques. You'll understand the code by working through the examples. The code has been broken down into small chunks (a few lines or a function at a time) to enable thorough discussion. As you progress, you will learn how to perform data analysis while exploring the functionalities of key data science Python packages, including pandas, SciPy, and scikit-learn. Finally, the book covers ethics and privacy concerns in data science and suggests resources for improving data science skills, as well as ways to stay up to date on new data science developments. By the end of the book, you should be able to comfortably use Python for basic data science projects and should have the skills to execute the data science process on any data source. What you will learnUse Python data science packages effectivelyClean and prepare data for data science work, including feature engineering and feature selectionData modeling, including classic statistical models (such as t-tests), and essential machine learning algorithms, such as random forests and boosted modelsEvaluate model performanceCompare and understand different machine learning methodsInteract with Excel spreadsheets through PythonCreate automated data science reports through PythonGet to grips with text analytics techniquesWho this book is for The book is intended for beginners, including students starting or about to start a data science, analytics, or related program (e.g. Bachelor’s, Master’s, bootcamp, online courses), recent college graduates who want to learn new skills to set them apart in the job market, professionals who want to learn hands-on data science techniques in Python, and those who want to shift their career to data science. The book requires basic familiarity with Python. A "getting started with Python" section has been included to get complete novices up to speed.
Financial Data Analysis Using Python
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Author : Dmytro Zherlitsyn
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-12-26
Financial Data Analysis Using Python written by Dmytro Zherlitsyn and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-26 with Computers categories.
This book will introduce essential concepts in financial analysis methods & models, covering time-series analysis, graphical analysis, technical and fundamental analysis, asset pricing and portfolio theory, investment and trade strategies, risk assessment and prediction, and financial ML practices. The Python programming language and its ecosystem libraries, such as Pandas, NumPy, SciPy, statsmodels, Matplotlib, Seaborn, Scikit-learn, Prophet, and other data science tools will demonstrate these rooted financial concepts in practice examples. This book will also help you understand the concepts of financial market dynamics, estimate the metrics of financial asset profitability, predict trends, evaluate strategies, optimize portfolios, and manage financial risks. You will also learn data analysis techniques using the Python programming language to understand the basics of data preparation, visualization, and manipulation in the world of financial data. FEATURES • Illustrates financial data analysis using Python data science libraries & techniques • Uses Python visualization tools to justify investment and trading strategies • Covers asset pricing & portfolio management methods with Python
Natural Language Processing With Flair
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Author : Tadej Magajna
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-04-29
Natural Language Processing With Flair written by Tadej Magajna 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 2022-04-29 with Computers categories.
Learn how to solve practical NLP problems with the Flair Python framework, train sequence labeling models, work with text classifiers and word embeddings, and much more through hands-on practical exercises Key FeaturesBacked by the community and written by an NLP expertGet an understanding of basic NLP problems and terminologySolve real-world NLP problems with Flair with the help of practical hands-on exercisesBook Description Flair is an easy-to-understand natural language processing (NLP) framework designed to facilitate training and distribution of state-of-the-art NLP models for named entity recognition, part-of-speech tagging, and text classification. Flair is also a text embedding library for combining different types of embeddings, such as document embeddings, Transformer embeddings, and the proposed Flair embeddings. Natural Language Processing with Flair takes a hands-on approach to explaining and solving real-world NLP problems. You'll begin by installing Flair and learning about the basic NLP concepts and terminology. You will explore Flair's extensive features, such as sequence tagging, text classification, and word embeddings, through practical exercises. As you advance, you will train your own sequence labeling and text classification models and learn how to use hyperparameter tuning in order to choose the right training parameters. You will learn about the idea behind one-shot and few-shot learning through a novel text classification technique TARS. Finally, you will solve several real-world NLP problems through hands-on exercises, as well as learn how to deploy Flair models to production. By the end of this Flair book, you'll have developed a thorough understanding of typical NLP problems and you'll be able to solve them with Flair. What you will learnGain an understanding of core NLP terminology and conceptsGet to grips with the capabilities of the Flair NLP frameworkFind out how to use Flair's state-of-the-art pre-built modelsBuild custom sequence labeling models, embeddings, and classifiersLearn about a novel text classification technique called TARSDiscover how to build applications with Flair and how to deploy them to productionWho this book is for This Flair NLP book is for anyone who wants to learn about NLP through one of the most beginner-friendly, yet powerful Python NLP libraries out there. Software engineering students, developers, data scientists, and anyone who is transitioning into NLP and is interested in learning about practical approaches to solving problems with Flair will find this book useful. The book, however, is not recommended for readers aiming to get an in-depth theoretical understanding of the mathematics behind NLP. Beginner-level knowledge of Python programming is required to get the most out of this book.
Practical Machine Learning
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Author : Ally S. Nyamawe
language : en
Publisher: CRC Press
Release Date : 2025-02-07
Practical Machine Learning written by Ally S. Nyamawe and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-07 with Computers categories.
The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field. It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models. This is a core resource for students and instructors of machine learning and data science looking for a beginner-friendly material which offers real-world applications and takes ethical discussions into account. The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.
Python For Ai
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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2024-10-23
Python For Ai written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Computers categories.
"Python for AI: Applying Machine Learning in Everyday Projects" is a comprehensive guide designed for anyone keen to delve into the transformative world of artificial intelligence using the potent yet accessible Python programming language. This book meticulously covers essential AI concepts, offering readers a structured path from understanding basic Python syntax to implementing sophisticated machine learning models. With a blend of foundational theories and practical applications, each chapter deftly guides readers through relevant techniques and tools, such as TensorFlow, Keras, and scikit-learn, that are crucial for modern AI development. Whether you are a beginner taking your first steps into AI or someone with programming experience seeking to expand your skill set, this book ensures you are equipped with the knowledge needed to tackle real-world challenges. It goes beyond mere theory, providing insights into deploying and integrating AI models, handling large datasets, and effectively developing solutions applicable across various industries. By the end of this journey, readers will not only grasp the intricacies of AI projects but also gain the confidence to innovate and contribute significantly to the evolving landscape of artificial intelligence.
Python Automation Mastery
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Author : Rob Botwright
language : en
Publisher: Rob Botwright
Release Date : 2023
Python Automation Mastery written by Rob Botwright and has been published by Rob Botwright this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Technology & Engineering categories.
🚀 PYTHON AUTOMATION MASTERY: From Novice to Pro Book Bundle 🚀 Are you ready to unlock the full potential of Python for automation? Look no further than the "Python Automation Mastery" book bundle, a comprehensive collection designed to take you from a beginner to an automation pro! 📘 Book 1 - Python Automation Mastery: A Beginner's Guide · Perfect for newcomers to programming and Python. · Learn Python fundamentals and the art of automation. · Start automating everyday tasks right away! 📗 Book 2 - Python Automation Mastery: Intermediate Techniques · Take your skills to the next level. · Discover web scraping, scripting, error handling, and data manipulation. · Tackle real-world automation challenges with confidence. 📙 Book 3 - Python Automation Mastery: Advanced Strategies · Explore advanced automation concepts. · Master object-oriented programming and external libraries. · Design and implement complex automation projects. 📕 Book 4 - Python Automation Mastery: Expert-Level Solutions · Become an automation architect. · Handle high-level use cases in AI, network security, and data analysis. · Elevate your automation skills to expert status. 🌟 What Makes This Bundle Special? · Comprehensive journey from novice to pro in one bundle. · Easy-to-follow, step-by-step guides in each book. · Real-world examples and hands-on exercises. · Learn ethical automation practices and best strategies. · Access a treasure trove of automation knowledge. 🚀 Why Python? Python is the go-to language for automation due to its simplicity and versatility. Whether you're looking to streamline everyday tasks or tackle complex automation challenges, Python is your ultimate tool. 📈 Invest in Your Future Automation skills are in high demand across industries. By mastering Python automation, you'll enhance your career prospects, supercharge your productivity, and become a sought-after automation expert. 📚 Grab the Complete Bundle Now! Don't miss out on this opportunity to become a Python automation master. Get all four books in one bundle and embark on your journey from novice to pro. Buy now and transform your Python skills into automation mastery!
Natural Language Processing With Python
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Author : Cuantum Technologies LLC
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-01-16
Natural Language Processing With Python written by Cuantum Technologies LLC 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 2025-01-16 with Computers categories.
Learn NLP with Python through practical exercises, advanced topics like transformers, and real-world projects such as chatbots and dashboards. A comprehensive guide for mastering NLP techniques. Key Features A comprehensive guide to processing, analyzing, and modeling human language with Python Real-world projects that reinforce NLP concepts, including chatbot design and sentiment analysis Foundational and advanced NLP techniques for practical applications in diverse domains Book DescriptionEmbark on a comprehensive journey to master natural language processing (NLP) with Python. Begin with foundational concepts like text preprocessing, tokenization, and key Python libraries such as NLTK, spaCy, and TextBlob. Explore the challenges of text data and gain hands-on experience in cleaning, tokenizing, and building basic NLP pipelines. Early chapters provide practical exercises to solidify your understanding of essential techniques. Advance to sophisticated topics like feature engineering using Bag of Words, TF-IDF, and embeddings like Word2Vec and BERT. Delve into language modeling with RNNs, syntax parsing, and sentiment analysis, learning to apply these techniques in real-world scenarios. Chapters on topic modeling and text summarization equip you to extract insights from data, while transformer-based models like BERT take your skills to the next level. Each concept is paired with Python-based examples, ensuring practical mastery. The final chapters focus on real-world projects, such as developing chatbots, sentiment analysis dashboards, and news aggregators. These hands-on applications challenge you to design, train, and deploy robust NLP solutions. With its structured approach and practical focus, this book equips you to confidently tackle real-world NLP challenges and innovate in the field.What you will learn Clean and preprocess text data using Python effectively Master tokenization techniques for words, sentences, and characters Build robust NLP pipelines with feature engineering methods Implement sentiment analysis with machine learning models Perform topic modeling using LDA, LSA, and other algorithms Develop chatbots and dashboards for real-world applications Who this book is for This book is ideal for students, researchers, and professionals in machine learning, data science, and artificial intelligence who want to master NLP. Beginners will benefit from the step-by-step introduction to text processing and feature engineering, while experienced practitioners can explore advanced topics like transformers and real-world projects. Basic knowledge of Python and familiarity with programming concepts are recommended to fully utilize the content. Enthusiasts with a passion for language technology will also find this guide valuable for building practical NLP applications.
Scikit Learn Unleashed A Comprehensive Guide To Machine Learning With Python
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Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-09
Scikit Learn Unleashed A Comprehensive Guide To Machine Learning With Python written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
"Scikit-Learn Unleashed: A Comprehensive Guide to Machine Learning with Python" is your ultimate roadmap to mastering one of Python's most robust machine learning libraries. This guide is perfect for those beginning their journey into machine learning as well as seasoned experts looking to broaden their expertise and refine their techniques. Spanning ten meticulously crafted chapters, this book delves deep into Scikit-Learn's extensive offerings, from foundational concepts to advanced applications. You'll begin your journey with essential machine learning principles and data preprocessing, before advancing to explore both supervised and unsupervised learning techniques. The book also offers insightful guidance on advanced model tuning and customization to ensure an all-encompassing understanding of machine learning. Every chapter is a stepping stone, building on prior knowledge to introduce complex ideas seamlessly with real-world examples that bring theoretical concepts to life. You'll learn to tackle data preprocessing challenges, apply diverse regression and classification algorithms, harness the potential of unsupervised learning, and enhance model performance through ensemble techniques. Moreover, the book covers essential topics like managing text data, model evaluation and selection, dimensionality reduction, and sophisticated tuning for finely customized models. "Scikit-Learn Unleashed" is more than just a tutorial; it is a treasure trove of insights, best practices, and actionable examples. It serves as an indispensable resource for data scientists, machine learning engineers, analysts, and anyone committed to unlocking the power of data through machine learning. Begin your journey with Scikit-Learn and empower yourself to solve complex, real-world problems with confidence and expertise.