BOOKS - Mathematical Analysis of Machine Learning Algorithms
Mathematical Analysis of Machine Learning Algorithms - Tong Zhang August 10, 2023 PDF  BOOKS
ECO~31 kg CO²

2 TON

Views
51792

Telegram
 
Mathematical Analysis of Machine Learning Algorithms
Author: Tong Zhang
Year: August 10, 2023
Format: PDF
File size: PDF 8.7 MB
Language: English



Pay with Telegram STARS
Mathematical Analysis of Machine Learning Algorithms In today's rapidly evolving technological landscape, it is crucial to comprehend the development of machine learning algorithms and their impact on modern society. As technology continues to advance at an unprecedented pace, understanding the underlying principles that drive this evolution is essential for humanity's survival and unity. In his groundbreaking book, "Mathematical Analysis of Machine Learning Algorithms [Author Name] delves into the intricacies of mathematical theory to provide a deep understanding of the current algorithms and inspire principled approaches for future innovation. The book is designed for students and researchers in the field of artificial intelligence, offering a self-contained text that covers the main mathematical techniques used to analyze machine learning algorithms. The author masterfully guides readers through the analysis of supervised learning algorithms in the iid setting, the analysis of neural networks, and the examination of machine learning algorithms in the sequential decision-making process. By exploring these topics, readers will gain a solid foundation in the basic mathematical tools needed to evaluate various concrete algorithms and their applications. The first chapter introduces the fundamental concepts of machine learning, providing a seamless transition into the more advanced topics covered throughout the book. The author presents a detailed explanation of the mathematical framework for analyzing machine learning algorithms, emphasizing the significance of understanding the underlying principles driving technological advancements.
''
機械学習アルゴリズムの数学的分析今日、急速に進化している技術的状況では、機械学習アルゴリズムの発展とその現代社会への影響を理解することが不可欠です。テクノロジーが前例のないペースで進歩し続ける中で、この進化を推進する原理を理解することは人類の生存と団結に不可欠です。彼の画期的な著書「機械学習アルゴリズムの数学的分析」では、現在のアルゴリズムを深く理解し、将来のイノベーションのための原則的なアプローチを促すために、数学理論の複雑さを掘り下げています。この本は、人工知能の分野の学生や研究者を対象としており、機械学習アルゴリズムの分析に使用される基本的な数学的手法を網羅した自己完結型のテキストを提供しています。著者は、iidの設定における教師との学習アルゴリズムの分析、ニューラルネットワークの分析、連続的な意思決定の過程における機械学習アルゴリズムの検討を通して読者を巧みに導きます。これらのトピックを研究することにより、読者はさまざまな特定のアルゴリズムとそのアプリケーションを評価するために必要な基本的な数学的ツールの基礎を持つことになります。第1章では、基本的な機械学習の概念を紹介し、本書全体でカバーされているより高度なトピックへのシームレスな移行を提供します。機械学習アルゴリズムの解析の数学的基礎を詳しく説明し、技術の進歩に寄与する基本原理を理解することの重要性を強調している。

You may also be interested in:

Mathematical Analysis of Machine Learning Algorithms
Mathematical Analysis of Machine Learning Algorithms
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
Mathematical Analysis for Machine Learning and Data Mining
Introduction to Machine Learning with R Rigorous Mathematical Analysis
Mastering Classification Algorithms for Machine Learning: Learn how to apply Classification algorithms for effective Machine Learning solutions (English Edition)
Unsupervised Machine Learning in Python Master Data Science and Machine Learning with Cluster Analysis, Gaussian Mixture Models, and Principal Components Analysis
Machine Learning for Business How to Build Artificial Intelligence through Concepts of Statistics, Algorithms, Analysis, and Data Mining
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
Machine Learning An In-Depth Beginners Guide into the Essentials of Machine Learning Algorithms
Hands-On Machine Learning with Scikit-Learn and Scientific Python Toolkits: A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
Python Machine Learning: Leveraging Python for Implementing Machine Learning Algorithms and Applications (2023 Guide)
Computer Programming This Book Includes Machine Learning for Beginners, Machine Learning with Python, Deep Learning with Python, Python for Data Analysis
Machine Learning For Beginners Step-by-Step Guide to Machine Learning, a Beginners Approach to Artificial Intelligence, Big Data, Basic Python Algorithms, and Techniques for Business (Practical Exampl
Machine Learning for Emotion Analysis in Python: Build AI-powered tools for analyzing emotion using natural language processing and machine learning
Machine Learning Step-by-Step Guide To Implement Machine Learning Algorithms with Python
Bio-inspired Algorithms in Machine Learning and Deep Learning for Disease Detection
Machine Learning Master Supervised and Unsupervised Learning Algorithms with Real Examples
Learning Kernel Classifiers: Theory and Algorithms (Adaptive Computation and Machine Learning)
Elements of Causal Inference: Foundations and Learning Algorithms (Adaptive Computation and Machine Learning series)
Machine Learning: Master Supervised and Unsupervised Learning Algorithms with Real Examples (English Edition)
Machine Learning with Python A Comprehensive Guide To Algorithms, Deep Learning Techniques, And Practical Applications
Hands-on Supervised Learning with Python Learn How to Solve Machine Learning Problems with Supervised Learning Algorithms
Learning Genetic Algorithms with Python Empower the Performance of Machine Learning and AI Models with the Capabilities of a Powerful Search Algorithm
Image Processing and Machine Learning, Volume 2 Advanced Topics in Image Analysis and Machine Learning
Machine Learning: Fundamental Algorithms for Supervised and Unsupervised Learning With Real-World Applications (Advanced Data Analytics Book 1)
Ultimate Java for Data Analytics and Machine Learning: Unlock Java|s Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j (English Edition)
Ultimate Java for Data Analytics and Machine Learning Unlock Java|s Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j
Ultimate Java for Data Analytics and Machine Learning Unlock Java|s Ecosystem for Data Analysis and Machine Learning Using WEKA, JavaML, JFreeChart, and Deeplearning4j
Machine Learning and Deep Learning in Neuroimaging Data Analysis
Machine Learning and Deep Learning in Neuroimaging Data Analysis
Machine Learning Algorithms Simplified
MACHINE LEARNING ALGORITHMS SIMPLIFIED
Machine Learning Algorithms Simplified
Machine Learning Algorithms in Depth
Machine Learning For Beginners Guide Algorithms Supervised & Unsupervsied Learning. Decision Tree & Random Forest Introduction
Understanding Machine Learning From Theory to Algorithms
Machine Learning Algorithms Using Python Programming
Machine Learning Algorithms From Scratch with Python
Metaheuristics for Machine Learning Algorithms and Applications