Python Pour La Data Science

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Python En Pratique Pour Le Data Scientist

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Author : Patrice Rey
language : fr
Publisher: BoD - Books on Demand
Release Date : 2024-12-10

Python En Pratique Pour Le Data Scientist written by Patrice Rey and has been published by BoD - Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-10 with Computers categories.

Python s'est imposé ces dernières années comme un langage de programmation incontournable dans de nombreux domaines. En science des données (data science), il se distingue comme un outil essentiel pour mener à bien des projets complexes grâce à son caractère universel. Il constitue aujourd'hui l'outil de choix pour la création de prototypes et un allié incontournable dans les domaines du big data, du machine learning, du deep learning et de l'intelligence artificielle. Cet ouvrage a pour but de vous accompagner dans la découverte de Python, un langage à la fois simple d'utilisation et puissant pour les utilisateurs travaillant avec les données. L'objectif est de vous fournir les connaissances nécessaires pour comprendre et maitriser Python dans le contexte de la data science. Pour quiconque aspire à devenir data scientist ou l'est déjà, la maitrise de Python est désormais un impératif.

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language : en
Publisher: BoD - Books on Demand
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written by and has been published by BoD - Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.

Hands On Data Science With Anaconda

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Author : Yuxing Yan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-05-31

Hands On Data Science With Anaconda written by Yuxing Yan 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 2018-05-31 with Computers categories.

Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda Key Features -Use Anaconda to find solutions for clustering, classification, and linear regression -Analyze your data efficiently with the most powerful data science stack -Use the Anaconda cloud to store, share, and discover projects and libraries Book Description Anaconda is an open source platform that brings together the best tools for data science professionals with more than 100 popular packages supporting Python, Scala, and R languages. Hands-On Data Science with Anaconda gets you started with Anaconda and demonstrates how you can use it to perform data science operations in the real world. The book begins with setting up the environment for Anaconda platform in order to make it accessible for tools and frameworks such as Jupyter, pandas, matplotlib, Python, R, Julia, and more. You’ll walk through package manager Conda, through which you can automatically manage all packages including cross-language dependencies, and work across Linux, macOS, and Windows. You’ll explore all the essentials of data science and linear algebra to perform data science tasks using packages such as SciPy, contrastive, scikit-learn, Rattle, and Rmixmod. Once you’re accustomed to all this, you’ll start with operations in data science such as cleaning, sorting, and data classification. You’ll move on to learning how to perform tasks such as clustering, regression, prediction, and building machine learning models and optimizing them. In addition to this, you’ll learn how to visualize data using the packages available for Julia, Python, and R. What you will learn Perform cleaning, sorting, classification, clustering, regression, and dataset modeling using Anaconda Use the package manager conda and discover, install, and use functionally efficient and scalable packages Get comfortable with heterogeneous data exploration using multiple languages within a project Perform distributed computing and use Anaconda Accelerate to optimize computational powers Discover and share packages, notebooks, and environments, and use shared project drives on Anaconda Cloud Tackle advanced data prediction problems Who this book is for Hands-On Data Science with Anaconda is for you if you are a developer who is looking for the best tools in the market to perform data science. It’s also ideal for data analysts and data science professionals who want to improve the efficiency of their data science applications by using the best libraries in multiple languages. Basic programming knowledge with R or Python and introductory knowledge of linear algebra is expected.

Humanities Data In R

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Author : Taylor Arnold
language : en
Publisher: Springer Nature
Release Date : 2024-07-22

Humanities Data In R written by Taylor Arnold and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-22 with Computers categories.

This book teaches readers to integrate data analysis techniques into humanities research practices using the R programming language. Methods for general-purpose visualization and analysis are introduced first, followed by domain-specific techniques for working with networks, text, geospatial data, temporal data, and images. The book is designed to be a bridge between quantitative and qualitative methods, individual and collaborative work, and the humanities and social sciences. The second edition of the text is a significant revision, with almost every aspect of the text rewritten in some way. The most notable difference is the incorporation of new R packages such as ggplot2 and dplyr that center broad data-science concepts. This 2nd edition of Humanities Data with R does not presuppose background programming experience. Early chapters take readers from R set-up to exploratory data analysis, with one chapter dedicated to each stage of the data-science pipeline (data collection, visualization, manipulation, and relational joins). Following this, text analysis, networks, temporal data, geospatial data, and image analysis each have a dedicated chapter. These are grounded in examples to move readers beyond the intimidation of adding new tools to their research. The final section of the book extends the core material with additional computer science techniques for processing large datasets. Everything is hands-on: image analysis is explained using digitized photographs from the 1930s, and networks are applied to page links on Wikipedia. After working through these examples with the provided data, code and book website, readers are prepared to apply new methods to their own work. The open source R programming language, with its myriad packages and popularity within the sciences and social sciences, is particularly well-suited to working with humanities data. R packages are also highlighted in an appendix. The methodology will have wide application in classrooms and self-study for the humanities, but also for use in linguistics, anthropology, and political science. Outside the classroom, this intersection of humanities and computing is particularly relevant for research and new modes of dissemination across archives, museums and libraries.

Data Science For Librarians

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Author : Yunfei Du
language : en
Publisher: Bloomsbury Publishing USA
Release Date : 2020-03-26

Data Science For Librarians written by Yunfei Du and has been published by Bloomsbury Publishing USA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-26 with Language Arts & Disciplines categories.

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.

Practical Statistics For Data Scientists

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Author : Peter Bruce
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-05-10

Practical Statistics For Data Scientists written by Peter Bruce and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-10 with Computers categories.

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Artificial Intelligence Big Data Iot And Block Chain In Healthcare From Concepts To Applications

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Author : Yousef Farhaoui
language : en
Publisher: Springer Nature
Release Date : 2024-08-13

Artificial Intelligence Big Data Iot And Block Chain In Healthcare From Concepts To Applications written by Yousef Farhaoui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-13 with Computers categories.

This book covers a wide range of topics related to the integration of Artificial Intelligence, Big Data, IoT, and Blockchain: From Concepts to Applications. It begins by establishing a solid foundation and introducing the concepts and principles of each technology. The subsequent chapters delve into the various applications and use cases, providing readers with real-world examples of how AI, IoT, and Blockchain can be leveraged to address key challenges in Smart Environments. Data is becoming an increasingly decisive resource in modern societies, economies, and governmental organizations. Data science, Artificial Intelligence, and Smart Environments inspire novel techniques and theories drawn from mathematics, statistics, information theory, computer science, and social science. This book reviews the state of the art of big data analysis, Artificial Intelligence, and Smart Environments. It includes issues that pertain to signal processing, probability models, machine learning, data mining, databases, data engineering, pattern recognition, visualization, predictive analytics, data warehousing, data compression, computer programming, smart city, etc. The papers in this book were the outcome of research conducted in this field of study. The latter makes use of applications and techniques related to data analysis in general and big data and smart cities in particular. The authors hope that this book serves as a valuable resource and guide for readers, empowering them to navigate the intricate landscape of Artificial Intelligence, IoT, and Blockchain in Smart Environments. Let the authors embark on this transformative journey together, as the authors explore the concepts and applications that hold the potential to shape the future of Smart Environments. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers, and industrial researchers, as well as anyone interested in big data analysis and Artificial Intelligence.

Proceedings Of The 7th International Conference On The Applications Of Science And Mathematics 2021

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Author : Aida Binti Mustapha
language : en
Publisher: Springer Nature
Release Date : 2022-06-28

Proceedings Of The 7th International Conference On The Applications Of Science And Mathematics 2021 written by Aida Binti Mustapha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Science categories.

This book presents peer-reviewed articles and recent advances on the potential applications of Science and Mathematics for future technologies, from the 7th International Conference on the Applications of Science and Mathematics (SCIEMATHIC 2021), held in Malaysia. It provides an insight about the leading trends in sustainable Science and Technology. The world is looking for sustainable solutions to problems more than ever. The synergistic approach of mathematicians, scientists and engineers has undeniable importance for future technologies. With this viewpoint, SCIEMATHIC 2021 has the theme “Quest for Sustainable Science and Mathematics for Future Technologies”. The conference brings together physicists, mathematicians, statisticians and data scientists, providing a platform to find sustainable solutions to major problems around us. The works presented here are suitable for professionals and researchers globally in making the world a better and sustainable place.

Machine Learning Optimization And Data Science

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Author : Giuseppe Nicosia
language : en
Publisher: Springer Nature
Release Date : 2023-03-08

Machine Learning Optimization And Data Science written by Giuseppe Nicosia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-08 with Computers categories.

This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.

Data Science For Migration And Mobility

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Author : Albert Ali Salah
language : en
Publisher: Liverpool University Press
Release Date : 2022-11-10

Data Science For Migration And Mobility written by Albert Ali Salah and has been published by Liverpool University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-10 with Reference categories.

Data Science for Migration and Mobility provides an interdisciplinary introduction to the usage of new data sources in migration and mobility research, including mobile phone records, social media content, satellite images, event and financial databases.