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  16. Free Download Colin Bamford, "Principles of International Financial Law Ed 3" English | ISBN: 0198832710 | 2020 | 368 pages | PDF | 27 MB This book explains the legal principles, rules, concepts, and developments that underpin the practice of financial law in common law countries, and by extension across the world. One of the aims of the book is to explain clearly the basis of the concepts applied by the common law to financial transactions. As part of this aim the third edition analyses in detail the interface between common-law and civil law approaches in areas such as the distinction between property and personal rights. The section on the ability of States to control the use of their money has also been substantially rewritten to address increasing demands in the US that sanctioned persons and states should be denied access to the US monetary system, recording both the increased incidence of activity by the US authorities, and also explaining in more detail the rationale of these actions. Since the last edition was written there have been a number of developments in the technology used in the financial markets that question the legal principles on which they operate. In particular, the impact of Distributed Ledger Technology (e.g. Blockchain) on the transfer of intangible assets and the effect on the rights of parties involved is considered from both a legal and practical position. Additionally, the legal implications of the use of cryptocurrencies, including their use as Initial Coin Offerings, are also considered. This is an essential work for both experienced lawyers and those who are relatively new to international financial law. It provides the more experienced lawyer with an aide memoire on the existing law and a reference source for new ideas when tackling innovative structures or products. For those new to practice or postgraduate students this book delivers a firm foundation upon which to build knowledge of the law and practice of financial law. Read more Rapidgator https://rg.to/file/224ae164381be58756e4dad9bc853e93/f5zk5.rar.html TakeFile https://takefile.link/u0tmn7xiukdl/f5zk5.rar.html Links are Interchangeable - Single Extraction
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  19. Free Download Principles of Data Science - Third Edition: A beginner's guide to essential math and coding skills for data fluency and machine learning by Sinan Ozdemir English | January 31, 2024 | ISBN: 1837636303 | 326 pages | EPUB | 8.77 Mb Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your dataKey FeaturesLearn practical data science combined with data theory to gain maximum insights from dataDiscover methods for deploying actionable machine learning pipelines while mitigating biases in data and modelsExplore actionable case studies to put your new skills to use immediatelyPurchase of the print or Kindle book includes a free PDF eBookBook Description Principles of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you'll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you'll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You'll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you'll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT.What you will learnMaster the fundamentals steps of data science through practical examplesBridge the gap between math and programming using advanced statistics and MLHarness probability, calculus, and models for effective data controlExplore transformative modern ML with large language modelsEvaluate ML success with impactful metrics and MLOpsCreate compelling visuals that convey actionable insightsQuantify and mitigate biases in data and ML modelsWho this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you'll find this book useful. Familiarity with Python programming will further enhance your learning experience.Table of ContentsData Science TerminologyTypes of DataThe Five Steps of Data ScienceBasic MathematicsImpossible or Improbable - A Gentle Introduction to ProbabilityAdvanced ProbabilityWhat are the Chances? An Introduction to StatisticsAdvanced StatisticsCommunicating DataHow to Tell if Your Toaster is Learning - Machine Learning EssentialsPredictions Don't Grow on Trees, or Do They?Introduction to Transfer Learning and Pre-trained ModelsMitigating Algorithmic Bias and Tackling Model and Data DriftAI GovernanceNavigating Real-World Data Science Case Studies in Action Rapidgator https://rg.to/file/7207ad7c92f6bccc639b0996b5e6a1d1/sxh7b.rar.html TakeFile https://takefile.link/0ee9ehe2flxr/sxh7b.rar.html Links are Interchangeable - Single Extraction
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