BOOKS - Practical Machine Learning with R Tutorials and Case Studies
Practical Machine Learning with R Tutorials and Case Studies - Carsten Lange 2024 PDF CRC Press BOOKS
ECO~15 kg CO²

1 TON

Views
97898

Telegram
 
Practical Machine Learning with R Tutorials and Case Studies
Author: Carsten Lange
Year: 2024
Pages: 369
Format: PDF
File size: 16.5 MB
Language: ENG



Pay with Telegram STARS
Practical Machine Learning with R Tutorials and Case Studies In today's rapidly evolving technological landscape, it is crucial to understand the process of technology evolution and its impact on humanity. As machines continue to advance, it is essential to develop a personal paradigm for perceiving the technological process of developing modern knowledge. This paradigm will serve as the basis for the survival of humanity and the unification of people in a warring state. To achieve this, we must embrace machine learning and artificial intelligence (AI) as they play an increasingly significant role in our lives. Practical Machine Learning with R Tutorials and Case Studies is a comprehensive guide tailored for students in business and economics. This handson approach focuses on practical applications rather than complex mathematical concepts, making it accessible to those without advanced mathematics knowledge such as matrix algebra or calculus. The author introduces machine learning algorithms using the widely used R language for statistical analysis, ensuring a unified experience across various models. The book leverages the tidymodels package, an extension of R that simplifies data processing and model workflows, making it easy for beginners to learn the language. With no prior programming skills required, this dynamic learning experience empowers students and instructors alike with a practical and accessible approach to machine learning in business and economics.
Практическое машинное обучение с R Tutorials и тематические исследования В современном быстро развивающемся технологическом ландшафте крайне важно понимать процесс эволюции технологий и его влияние на человечество. По мере того, как машины продолжают продвигаться вперед, важно выработать личностную парадигму восприятия технологического процесса развития современных знаний. Эта парадигма послужит основой для выживания человечества и объединения людей в воюющем государстве. Чтобы достичь этого, мы должны принять машинное обучение и искусственный интеллект (ИИ), поскольку они играют все более значимую роль в нашей жизни. Практическое машинное обучение с R Tutorials и Case Studies - это комплексное руководство, разработанное специально для студентов в области бизнеса и экономики. Этот подход сосредоточен на практических приложениях, а не на сложных математических концепциях, что делает его доступным для тех, кто не имеет продвинутых математических знаний, таких как матричная алгебра или исчисление. Автор вводит алгоритмы машинного обучения, использующие широко используемый язык R для статистического анализа, обеспечивая единый опыт по различным моделям. Книга использует пакет tidymodels, расширение R, которое упрощает обработку данных и моделирует рабочие процессы, облегчая новичкам изучение языка. Без предварительных навыков программирования этот динамичный опыт обучения дает студентам и преподавателям практический и доступный подход к машинному обучению в бизнесе и экономике.
Apprentissage automatique pratique avec R Tutorials et études de cas Dans le paysage technologique en évolution rapide d'aujourd'hui, il est essentiel de comprendre le processus d'évolution de la technologie et son impact sur l'humanité. Au fur et à mesure que les machines progressent, il est important de développer un paradigme personnel de la perception du processus technologique du développement des connaissances modernes. Ce paradigme servira de base à la survie de l'humanité et à l'unification des hommes dans un État en guerre. Pour y parvenir, nous devons adopter l'apprentissage automatique et l'intelligence artificielle (IA), car ils jouent un rôle de plus en plus important dans nos vies. L'apprentissage machine pratique avec R Tutorials et Case Studies est un guide complet conçu spécialement pour les étudiants en affaires et en économie. Cette approche se concentre sur des applications pratiques plutôt que sur des concepts mathématiques complexes, ce qui la rend accessible à ceux qui n'ont pas de connaissances mathématiques avancées telles que l'algèbre matricielle ou le calcul. L'auteur introduit des algorithmes d'apprentissage automatique utilisant le langage R largement utilisé pour l'analyse statistique, fournissant une expérience unifiée sur différents modèles. livre utilise le paquet tidymodels, une extension R qui simplifie le traitement des données et simule les flux de travail, facilitant l'apprentissage de la langue pour les débutants. Sans savoir-faire préalable en programmation, cette expérience d'apprentissage dynamique offre aux étudiants et aux enseignants une approche pratique et abordable de l'apprentissage automatique dans les affaires et l'économie.
Práctica Machine arning con R Tutorials y estudios de caso En el panorama tecnológico en rápida evolución actual, es fundamental comprender el proceso de evolución de la tecnología y su impacto en la humanidad. A medida que las máquinas continúan avanzando, es importante desarrollar un paradigma personal de percepción del proceso tecnológico del desarrollo del conocimiento moderno. Este paradigma servirá de base para la supervivencia de la humanidad y la unificación de los seres humanos en un Estado en guerra. Para lograrlo, debemos adoptar el aprendizaje automático y la inteligencia artificial (IA), ya que juegan un papel cada vez más significativo en nuestras vidas. aprendizaje automático práctico con R Tutorials y Case Studies es una guía integral diseñada específicamente para estudiantes de negocios y economía. Este enfoque se centra en aplicaciones prácticas en lugar de conceptos matemáticos complejos, lo que lo hace accesible para aquellos que no tienen conocimientos matemáticos avanzados como álgebra matricial o cálculo. autor introduce algoritmos de aprendizaje automático que utilizan el lenguaje R ampliamente utilizado para el análisis estadístico, proporcionando una única experiencia en diferentes modelos. libro utiliza el paquete tidymodels, una extensión de R que simplifica el procesamiento de datos y modela los flujos de trabajo, facilitando el aprendizaje de idiomas a los principiantes. n conocimientos previos de programación, esta dinámica experiencia de aprendizaje ofrece a estudiantes y profesores un enfoque práctico y asequible del aprendizaje automático en las empresas y la economía.
Praktisches maschinelles rnen mit R Tutorials und Fallstudien In der heutigen schnelllebigen Technologielandschaft ist es entscheidend, den technologischen Evolutionsprozess und seine Auswirkungen auf die Menschheit zu verstehen. Wenn Maschinen weiter voranschreiten, ist es wichtig, ein persönliches Paradigma für die Wahrnehmung des technologischen Prozesses der Entwicklung des modernen Wissens zu entwickeln. Dieses Paradigma wird als Grundlage für das Überleben der Menschheit und die Vereinigung der Menschen in einem kriegführenden Staat dienen. Um dies zu erreichen, müssen wir maschinelles rnen und künstliche Intelligenz (KI) akzeptieren, da sie eine immer wichtigere Rolle in unserem ben spielen. Praktisches maschinelles rnen mit R Tutorials und Case Studies ist ein umfassender itfaden, der speziell für Studenten aus Wirtschaft und Wirtschaft entwickelt wurde. Dieser Ansatz konzentriert sich auf praktische Anwendungen und nicht auf komplexe mathematische Konzepte, die es für diejenigen zugänglich machen, die keine fortgeschrittenen mathematischen Kenntnisse wie Matrixalgebra oder Kalkül haben. Der Autor stellt Algorithmen für maschinelles rnen vor, die die weit verbreitete R-Sprache für statistische Analysen verwenden und eine einheitliche Erfahrung über verschiedene Modelle hinweg bieten. Das Buch verwendet das Tidymodels-Paket, eine R-Erweiterung, die die Datenverarbeitung vereinfacht und Arbeitsabläufe modelliert, sodass Anfänger die Sprache leichter lernen können. Ohne vorherige Programmierkenntnisse bietet diese dynamische rnerfahrung Schülern und hrern einen praktischen und erschwinglichen Ansatz für maschinelles rnen in Wirtschaft und Wirtschaft.
''
R Öğreticiler ve Vaka Çalışmaları ile Uygulamalı Makine Öğrenimi Günümüzün hızla gelişen teknolojik ortamında, teknolojinin evrimini ve insanlık üzerindeki etkisini anlamak çok önemlidir. Makineler ilerlemeye devam ettikçe, modern bilginin gelişiminin teknolojik sürecinin algılanması için kişisel bir paradigma geliştirmek önemlidir. Bu paradigma, insanlığın hayatta kalması ve insanların savaşan bir durumda birleşmesi için temel oluşturacaktır. Bunu başarmak için, makine öğrenimini ve yapay zekayı (AI) hayatımızda giderek daha anlamlı bir rol oynadıkları için benimsemeliyiz. R Tutorials ve Case Studies ile uygulamalı makine öğrenimi, özellikle işletme ve ekonomi öğrencileri için tasarlanmış kapsamlı bir kılavuzdur. Bu yaklaşım, karmaşık matematiksel kavramlardan ziyade pratik uygulamalara odaklanır ve matris cebiri veya kalkülüs gibi gelişmiş matematiksel bilgiye sahip olmayanlar için erişilebilir olmasını sağlar. Yazar, istatistiksel analiz için yaygın olarak kullanılan R dilini kullanarak makine öğrenme algoritmalarını tanıtıyor ve farklı modellerde tek bir deneyim sunuyor. Kitap, veri işlemeyi basitleştiren ve iş akışlarını simüle eden ve yeni başlayanların dili öğrenmesini kolaylaştıran bir R uzantısı olan tidymodels paketini kullanıyor. Önceden programlama becerileri olmadan, bu dinamik öğrenme deneyimi öğrencilere ve öğretim üyelerine iş ve ekonomi alanında makine öğrenimi için pratik ve erişilebilir bir yaklaşım sunar.
التعلم الآلي العملي مع دروس R ودراسات الحالة في المشهد التكنولوجي سريع التطور اليوم، من الأهمية بمكان فهم تطور التكنولوجيا وتأثيرها على البشرية. مع استمرار الآلات في المضي قدمًا، من المهم تطوير نموذج شخصي لتصور العملية التكنولوجية لتطوير المعرفة الحديثة. وسيكون هذا النموذج أساسا لبقاء البشرية وتوحيد الشعوب في دولة متحاربة. لتحقيق ذلك، يجب أن نتبنى التعلم الآلي والذكاء الاصطناعي (AI) لأنهما يلعبان دورًا ذا مغزى متزايد في حياتنا. التعلم الآلي العملي مع R Tutorials و Case Studies هو دليل شامل مصمم خصيصًا للطلاب في مجال الأعمال والاقتصاد. يركز هذا النهج على التطبيقات العملية بدلاً من المفاهيم الرياضية المعقدة، مما يجعله في متناول أولئك الذين ليس لديهم معرفة رياضية متقدمة مثل جبر المصفوفة أو حساب التفاضل والتكامل. يقدم المؤلف خوارزميات التعلم الآلي باستخدام لغة R المستخدمة على نطاق واسع للتحليل الإحصائي، مما يوفر تجربة واحدة عبر نماذج مختلفة. يستخدم الكتاب حزمة tidymodels، وهي امتداد R يبسط معالجة البيانات ويحاكي سير العمل، مما يسهل على المبتدئين تعلم اللغة. بدون مهارات البرمجة السابقة، تمنح تجربة التعلم الديناميكية هذه الطلاب وأعضاء هيئة التدريس نهجًا عمليًا ويمكن الوصول إليه للتعلم الآلي في مجال الأعمال والاقتصاد.

You may also be interested in:

Programming Machine Learning Machine Learning Basics Concepts + Artificial Intelligence + Python Programming + Python Machine Learning
Programming Machine Learning Machine Learning Basics Concepts + Artificial Intelligence + Python Programming + Python Machine Learning
Computer Programming This Book Includes Machine Learning for Beginners, Machine Learning with Python, Deep Learning with Python, Python for Data Analysis
Programming With Python 4 Manuscripts - Deep Learning With Keras, Convolutional Neural Networks In Python, Python Machine Learning, Machine Learning With Tensorflow
Pragmatic Machine Learning with Python Learn How to Deploy Machine Learning Models in Production
Machine Learning for Finance Master Financial Strategies with Python-Powered Machine Learning
Machine Learning for Finance Master Financial Strategies with Python-Powered Machine Learning
Machine Learning, Animated (Chapman and Hall CRC Machine Learning and Pattern Recognition)
Machine Learning for Absolute Beginners An Absolute beginner’s guide to learning and understanding machine learning successfully
Machine Learning for Civil and Environmental Engineers: A Practical Approach to Data-Driven Analysis, Explainability, and Causality
Practical Automated Machine Learning on Azure Using AutoML to Build and Deploy Intelligent Solutions (Early Release)
Feature Engineering for Modern Machine Learning with Scikit-Learn Advanced Data Science and Practical Applications
Machine Learning for Civil and Environmental Engineers A Practical Approach to Data-driven Analysis, Explainability, and Causality
Machine Learning with Python The Ultimate Guide to Learn Machine Learning Algorithms. Includes a Useful Section about Analysis, Data Mining and Artificial Intelligence in Business Applications
Machine Learning Tutorial: Machine Learning Simply Easy Learning
Machine Learning The Ultimate Guide to Understand Artificial Intelligence and Big Data Analytics. Learn the Building Block Algorithms and the Machine Learning’s Application in the Modern Life
Probabilistic Machine Learning: An Introduction (Adaptive Computation and Machine Learning series)
Introduction to Machine Learning (Adaptive Computation and Machine Learning), 4th Edition
Machine Learning Interviews Kickstart Your Machine Learning and Data Career (Final)
Cloud Computing for Machine Learning and Cognitive Applications A Machine Learning Approach
Statistics for Machine Learning Implement Statistical methods used in Machine Learning using Python
Machine Learning An In-Depth Beginners Guide into the Essentials of Machine Learning Algorithms
Machine Learning Production Systems Engineering Machine Learning Models and Pipelines
Python Machine Learning Machine Learning and Deep Learning with Python, scikit-learn and Tensorflow
Python Machine Learning A Complete Guide for Beginners on Machine Learning and Deep Learning with Python
Machine Learning for Beginners An Introduction to Artificial Intelligence and Machine Learning
Machine Learning Interviews: Kickstart Your Machine Learning and Data Career
Mastering OpenCV with Python Use NumPy, Scikit, TensorFlow, and Matplotlib to learn Advanced algorithms for Machine Learning through a set of Practical Projects
Machine Learning For Beginners A Math Free Introduction for Business and Individuals to Machine Learning, Big Data, Data Science, and Neural Networks
Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Ultimate MLOps for Machine Learning Models Use Real Case Studies to Efficiently Build, Deploy, and Scale Machine Learning Pipelines with MLOps
Unsupervised Machine Learning in Python Master Data Science and Machine Learning with Cluster Analysis, Gaussian Mixture Models, and Principal Components Analysis
Machine Learning Hero Master Data Science with Python Essentials Machine Learning with Python Hands-On Guide from Beginner to Expert (Mastering the AI Revolution Book 1)
Hacker|s Guide to Machine Learning with Python Hands-on guide to solving real-world Machine Learning problems with Scikit-Learn, TensorFlow 2, and Keras
Python Machine Learning Is The Complete Guide To Everything You Need To Know About Python Machine Learning Keras, Numpy, Scikit Learn, Tensorflow, With Useful Exercises and examples
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning
Python Machine Learning A Hands-On Beginner|s Guide to Effectively Understand Artificial Neural Networks and Machine Learning Using Python
Python Machine Learning Understand Python Libraries (Keras, NumPy, Scikit-lear, TensorFlow) for Implementing Machine Learning Models in Order to Build Intelligent Systems
Ultimate Machine Learning with ML.NET Build, Optimize, and Deploy Powerful Machine Learning Models for Data-Driven Insights with ML.NET, Azure Functions, and Web API
Data Science and Machine Learning Interview Questions Using R Crack the Data Scientist and Machine Learning Engineers Interviews with Ease