Python Machine Learning 2021 2022
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Python Machine Learning 2021 2022
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Author : Victor London
language : en
Publisher: Victor London
Release Date : 2021-06-08
Python Machine Learning 2021 2022 written by Victor London and has been published by Victor London this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-08 with categories.
★ 55% OFF for Bookstores! ★ If you are looking for a comprehensive guide that explains in a simple way how to manage machine learning and AI, please keep reading. What if you could make your own program, one that is able to learn by trial and error, or based on the information that you show it? What if you could get a program that could adapt and change based on the input of the user? And what if you were able to make all of this happen with the Python coding language, helping even beginner's work with more complicated codes? This is all possible with Python machine learning. This guidebook is going to take some time to look at Python machine learning and all of the neat things that you are able to do with it. Machine learning is a growing field, one that a lot of programmers want to spend their time on. But even though this sounds like a complicated part of technology to work with, you will find that with the help of the Python coding language, anyone can start writing their own codes in machine learning. This guidebook is going to take a look at all of the different topics that you need to know in order to get started with Python machine learning. Some of the topics that we will explore inside include: The basics of machine learning The difference between supervised and unsupervised machine learning. Setting up your new environment in the Python language. Data preprocessing with the help of machine learning. How to use Python coding to help with linear regression. Decision trees and random forests. How to work with support vector regression problems. Can machine learning really help with Naïve Bayes problems? Accelerated data analysis using the Python code. And so much more! If you have been interested in learning more about machine learning, and you want to be able to learn a few of the codes that can make it happen for you, make sure to check out this guidebook to help you get started!
Applications Of Ai And Machine Learning In Finance And Economics
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Author : Alessia Paccagnini
language : en
Publisher: Frontiers Media SA
Release Date : 2025-11-19
Applications Of Ai And Machine Learning In Finance And Economics written by Alessia Paccagnini and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-19 with Science categories.
This Research Topic is in collaboration with the Women in FinTech and AI 2024 conference. Extended versions of work presented at the conference are welcome. In today's rapidly evolving economic landscape, the integration of artificial intelligence (AI) in finance and economics has become paramount. AI, fueled by unprecedented computational power and sophisticated algorithms, has the potential to revolutionize decision-making processes, risk management, and predictive analytics within the financial sector. Its adaptive capabilities and data-driven insights contribute to more informed strategies, driving efficiency and innovation. Moreover, the era of big data has ushered in a new paradigm, where vast and diverse datasets serve as a cornerstone for informed decision-making. The intersection of big data and finance allows for a granular understanding of market dynamics, customer behavior, and economic trends. Harnessing the power of big data, alongside AI, not only empowers financial institutions to navigate complexities but also lays the foundation for sustainable and resilient financial systems in an interconnected global economy. We invite researchers and professionals to contribute to a special issue of Frontiers in Artificial Intelligence dedicated to the intersection of artificial intelligence and economics and finance. This special issue aims to explore cutting-edge advancements in various areas, including but not limited to Big Data applied to finance, natural language processing in economics, digital finance and sustainability, AI for financial markets, and blockchain applications. We welcome submissions on a wide range of topics, including: • Big Data applications in finance and economics • Natural language processing in economic and financial contexts • Digital finance and its implications for sustainability • Artificial intelligence in financial markets • Blockchain applications in finance • Artificial intelligence for peer-to-peer finance • Network analysis in finance • Artificial intelligence in Green Finance and Climate Change • Behavioral finance
Trustworthy Artificial Intelligence In Industry And Society
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Author : Dimple Patil
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-17
Trustworthy Artificial Intelligence In Industry And Society written by Dimple Patil and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-17 with Computers categories.
Artificial Intelligence (AI) is evolving at an unprecedented rate, changing industries and reshaping social landscapes. However, the question still stands: how can we make sure that, even with this growth, AI stays ethical and trustworthy? In an effort to investigate this issue, the book Trustworthy Artificial Intelligence in Industry and Society provides a thorough analysis of AI's potential to promote resilience, accountability, and trust in a variety of contexts. Chapter 1 explores the essential need for transparent and interpretable AI systems, starting with the foundation of Explainable Artificial Intelligence (XAI) and laying the framework for fostering trust among users, stakeholders, and society at large. In Chapter 2, deep learning and machine learning are explored, along with their applications, methods, and implementation challenges. In Chapter 3, the book delves into the impact of artificial intelligence (AI) on Environmental, Social, and Governance (ESG) initiatives. It specifically highlights the applications of AI in the financial services and investment sectors. We look at the adoption and application of AI in the construction sector in Chapter 4, offering some insight into the drivers, patterns, and obstacles that will shape the technology's future. The use of AI to improve supply chain sustainability and revolutionize the transportation industry is covered in Chapters 5 and 6, with a focus on generative AI technologies and ethical issues. Chapter 7 explores how artificial intelligence is affecting customer relationship management, highlighting how sentiment analysis is transforming customer loyalty and experience. This book seeks to shed light on the opportunities and difficulties that artificial intelligence (AI) brings to business and society by exploring these areas.
The 22nd International Conference On Information Technology New Generations Itng 2025
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Author : Shahram Latifi
language : en
Publisher: Springer Nature
Release Date : 2025-05-08
The 22nd International Conference On Information Technology New Generations Itng 2025 written by Shahram Latifi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-08 with Computers categories.
This book covers technical contributions that have been submitted, reviewed and presented at the 22nd annual event of International conference on Information Technology: New Generations (ITNG) The applications of advanced information technology to such domains as astronomy, biology, education, geosciences, security and health care are among topics of relevance to ITNG. Visionary ideas, theoretical and experimental results, as well as prototypes, designs, and tools that help the information readily flow to the user are of special interest. Machine Learning, Robotics, High Performance Computing, and Innovative Methods of Computing are examples of related topics.
Intelligent Computing And Networking
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Author : George Ghinea
language : en
Publisher: Springer Nature
Release Date : 2025-02-15
Intelligent Computing And Networking written by George Ghinea and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-15 with Technology & Engineering categories.
This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2024), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 23–24, 2024. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in healthcare, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics, and blockchain technology.
Analytics In Finance And Risk Management
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Author : Nga Thi Hong Nguyen
language : en
Publisher: CRC Press
Release Date : 2023-12-26
Analytics In Finance And Risk Management written by Nga Thi Hong Nguyen and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-26 with Business & Economics categories.
This book presents contemporary issues and challenges in finance and risk management in a time of rapid transformation due to technological advancements. It includes research articles based on financial and economic data and intends to cover the emerging role of analytics in financial management, asset management, and risk management. Analytics in Finance and Risk Management covers statistical techniques for data analysis in finance. It explores applications in finance and risk management, covering empirical properties of financial systems. It addresses data science involving the study of statistical and computational models and includes basic and advanced concepts. The chapters incorporate the latest methodologies and challenges facing financial and risk management and illustrate related issues and their implications in the real world. The primary users of this book will include researchers, academicians, postgraduate students, professionals in engineering and business analytics, managers, consultants, and advisors in IT firms, financial markets, and services domains.
Knowledge Management And Artificial Intelligence For Growth
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Author : Isaias Bianchi
language : en
Publisher: Springer Nature
Release Date : 2024-09-20
Knowledge Management And Artificial Intelligence For Growth written by Isaias Bianchi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-20 with Computers categories.
This book delves into the intersection of Knowledge Management (KM) and Artificial Intelligence (AI). It explores their applications, challenges, and opportunities across various industries and regions. The approach is comprehensive, drawing insights from experts worldwide. The book offers fresh perspectives on using KM and AI as powerful tools for driving business success. It covers research opportunities, real-world case studies, and empirical investigations. Notably, it emphasizes the unique context of knowledge management in the southern hemisphere. The book spans a broad range of subjects, including knowledge absorption capacity as an internationalization driver, quality certification methods in the health sector, and the role of intellectual capital in Argentine tech companies. It also delves into machine learning techniques for property price estimation in Brazil and identity document verification in Peru. Professionals, scholars, and policymakers navigating the complex integration of KM and AI will find this book invaluable. By combining theoretical foundations with practical findings, it equips readers with the knowledge and tools needed for sustainable growth within their organizations.
Service Oriented Computing
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Author : Marco Aiello
language : en
Publisher: Springer Nature
Release Date : 2023-10-11
Service Oriented Computing written by Marco Aiello and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-11 with Computers categories.
This book constitutes the refereed proceedings of the 17th Symposium and Summer School, SummerSOC 2023, held in Heraklion, Crete, Greece, in June 25–July 1, 2023. The 6 full papers and 3 short papers presented in this book were carefully reviewed and selected from 27 submissions. They are organized in the following sections as follows: Distributed Systems; Smart; and Mixed Technologies.
Python Machine Learning For Beginners 2021
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Author : Steven Williams
language : en
Publisher:
Release Date : 2020-12-05
Python Machine Learning For Beginners 2021 written by Steven Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-05 with categories.
If you want to learn how to design and master different Machine Learning algorithms quickly and easily, then keep reading. We live in a world of data deluge where gigabytes of data are generated daily. It is possible that this data might not be very useful for our daily applications. Major setbacks in the use of such data may be due to the presence of loopholes in data links previously generated or the data might be too vast for the limited human mind. Machine learning in this book presents some of the solutions to the problems above. Being an introductory guide, expect to learn the various basics involved in Machine Learning and Python. This book provides an insight into the new world of big data, then behooves you to learn more about Machine Learning. With a detailed and concise overview of the fundamentals, along with the challenges and limitations currently being tackled by the pros, inside this comprehensive guide you will Learn the Fundamentals of Machine Learning which Are Being Developed and Advanced with Python What is Machine Learning and how it is applied in real-world situations Algorithms, in a Language that Requires No Prior Background in Python Discover best practices for evaluating and tuning models Discover the Details of the Supervised, Unsupervised, and Reinforcement Algorithms, which Serve as the Skeleton of Hundreds of Machine Learning Algorithms Being Developed Every Day Become Familiar with Data Science Technology, an Umbrella Term Used for the Cutting-Edge Technologies of Today Understand the Entire Process of Creating Neural Network Models on TensorFlow, Using Open Source Data Sets and real Python Code Uncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets Artificial Neural Networks And Much More! So what are you waiting for? Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Would You Like To Know More? Scroll up and click on the BUY NOW button to get your copy now!
Simulation Modeling And Analysis Sixth Edition
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Author : Averill M. Law
language : en
Publisher: McGraw Hill Professional
Release Date : 2025-02-21
Simulation Modeling And Analysis Sixth Edition written by Averill M. Law and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-21 with Technology & Engineering categories.
Comprehensive, state-of-the-art coverage of every important simulation technique This fully-revised book has the most comprehensive and up-to-date coverage of all aspects of a simulation study. Equally well suited for use in university courses, simulation practice, and self-study, the book offers clear and intuitive explanations as well as 300 figures, 218 examples, and 217 problems. You will get detailed discussions on modeling and simulation, simulation software, model verification and validation, input modeling, random-number and variate generation, statistical design and analysis of simulation experiments, experimental design, simulation optimization, agent-based simulation, machine learning, and much more. Authored by an operations research analyst and industrial engineer with more than 40 years of experience, Simulation Modeling and Analysis is widely regarded as the “bible” of simulation and now has more than 178,000 copies in print and 23,700 citations. This sixth edition has been streamlined, with several chapters downsized to eliminate outdated simulation programs or statistical techniques that are rarely used in practice and are unnecessarily complicated. Most analyses of simulation output data can now be done using three simple and familiar statistical formulas or expressions. A new chapter covers AI and machine learning and their application to simulation. Covers what are arguably the three most-innovative and popular simulation-software packages: AnyLogic, FlexSim, and Simio Includes a set of instructor’s resources Has been used at universities such as University of California-Berkeley, Stanford, Georgia Tech, Michigan, Cornell, Purdue, Virginia Tech, Penn State, Wisconsin, Columbia, Texas A&M, Washington, and Johns Hopkins Written by a world-class expert in the field and an experienced educator who has presented more than 550 simulation and statistics short courses in 20 countries