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Author: Manjunath.R
Publisher: Manjunath.R
ISBN:
Category : Antiques & Collectibles
Languages : en
Pages : 1238
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Book Description
The Scientific Compendium: A Comprehensive Reference for Data and Formulas The "Science Data Booklet" is an essential companion for students, researchers, and science enthusiasts alike, providing a comprehensive collection of key scientific data and information. This meticulously curated reference book serves as a treasure trove of facts, equations, and formulas from various scientific disciplines, designed to empower readers with the tools they need to excel in their scientific pursuits. Inside this invaluable compendium, readers will discover a wealth of information spanning the realms of physics, chemistry, biology, astronomy, and more. From fundamental constants to conversion factors, this book offers a concise and easily accessible compilation of scientific knowledge that is essential for scientific investigations, experiments, and calculations. Whether you are a student preparing for exams, a researcher seeking quick access to vital data, or a science enthusiast eager to delve deeper into the world of scientific knowledge, this book is your indispensable companion. With the help of this book, you can access a plethora of scientific knowledge at your fingertips, anytime and anywhere. In a world increasingly driven by scientific advancements, the "Science Data Booklet" serves as an invaluable resource for anyone seeking to navigate the complexities of scientific data. This book is not only a reference guide but also a catalyst for curiosity, inspiring readers to explore the wonders of the natural world and embark on their own scientific journeys. Unlock the power of scientific knowledge with the "Science Data Booklet" and embark on a fascinating voyage of discovery, innovation, and understanding.
Author: Manjunath.R
Publisher: Manjunath.R
ISBN:
Category : Antiques & Collectibles
Languages : en
Pages : 1238
Get Book Here
Book Description
The Scientific Compendium: A Comprehensive Reference for Data and Formulas The "Science Data Booklet" is an essential companion for students, researchers, and science enthusiasts alike, providing a comprehensive collection of key scientific data and information. This meticulously curated reference book serves as a treasure trove of facts, equations, and formulas from various scientific disciplines, designed to empower readers with the tools they need to excel in their scientific pursuits. Inside this invaluable compendium, readers will discover a wealth of information spanning the realms of physics, chemistry, biology, astronomy, and more. From fundamental constants to conversion factors, this book offers a concise and easily accessible compilation of scientific knowledge that is essential for scientific investigations, experiments, and calculations. Whether you are a student preparing for exams, a researcher seeking quick access to vital data, or a science enthusiast eager to delve deeper into the world of scientific knowledge, this book is your indispensable companion. With the help of this book, you can access a plethora of scientific knowledge at your fingertips, anytime and anywhere. In a world increasingly driven by scientific advancements, the "Science Data Booklet" serves as an invaluable resource for anyone seeking to navigate the complexities of scientific data. This book is not only a reference guide but also a catalyst for curiosity, inspiring readers to explore the wonders of the natural world and embark on their own scientific journeys. Unlock the power of scientific knowledge with the "Science Data Booklet" and embark on a fascinating voyage of discovery, innovation, and understanding.
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author: Avrim Blum
Publisher: Cambridge University Press
ISBN: 1108617360
Category : Computers
Languages : en
Pages : 433
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Book Description
This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.
Author: Carl Shan
Publisher:
ISBN: 9780692434871
Category :
Languages : en
Pages :
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Book Description
The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about career and personal success. You'll hear from a young woman who created her own data scientist curriculum, subsequently landing her a role in the field. Readers of this book will be left with war stories, wisdom and
Author: Vladimír Šucha
Publisher:
ISBN: 0128226900
Category : Electronic books
Languages : en
Pages : 290
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Book Description
Author: Laura Igual
Publisher: Springer
ISBN: 3319500171
Category : Computers
Languages : en
Pages : 227
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Book Description
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website.
Author: Dirk P. Kroese
Publisher: CRC Press
ISBN: 1000730778
Category : Business & Economics
Languages : en
Pages : 538
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Book Description
Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code
Author: Jike Chong
Publisher: Simon and Schuster
ISBN: 1638356807
Category : Computers
Languages : en
Pages : 823
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Book Description
A field guide for the unique challenges of data science leadership, filled with transformative insights, personal experiences, and industry examples. In How To Lead in Data Science you will learn: Best practices for leading projects while balancing complex trade-offs Specifying, prioritizing, and planning projects from vague requirements Navigating structural challenges in your organization Working through project failures with positivity and tenacity Growing your team with coaching, mentoring, and advising Crafting technology roadmaps and championing successful projects Driving diversity, inclusion, and belonging within teams Architecting a long-term business strategy and data roadmap as an executive Delivering a data-driven culture and structuring productive data science organizations How to Lead in Data Science is full of techniques for leading data science at every seniority level—from heading up a single project to overseeing a whole company's data strategy. Authors Jike Chong and Yue Cathy Chang share hard-won advice that they've developed building data teams for LinkedIn, Acorns, Yiren Digital, large asset-management firms, Fortune 50 companies, and more. You'll find advice on plotting your long-term career advancement, as well as quick wins you can put into practice right away. Carefully crafted assessments and interview scenarios encourage introspection, reveal personal blind spots, and highlight development areas. About the technology Lead your data science teams and projects to success! To make a consistent, meaningful impact as a data science leader, you must articulate technology roadmaps, plan effective project strategies, support diversity, and create a positive environment for professional growth. This book delivers the wisdom and practical skills you need to thrive as a data science leader at all levels, from team member to the C-suite. About the book How to Lead in Data Science shares unique leadership techniques from high-performance data teams. It’s filled with best practices for balancing project trade-offs and producing exceptional results, even when beginning with vague requirements or unclear expectations. You’ll find a clearly presented modern leadership framework based on current case studies, with insights reaching all the way to Aristotle and Confucius. As you read, you’ll build practical skills to grow and improve your team, your company’s data culture, and yourself. What's inside How to coach and mentor team members Navigate an organization’s structural challenges Secure commitments from other teams and partners Stay current with the technology landscape Advance your career About the reader For data science practitioners at all levels. About the author Dr. Jike Chong and Yue Cathy Chang build, lead, and grow high-performing data teams across industries in public and private companies, such as Acorns, LinkedIn, large asset-management firms, and Fortune 50 companies. Table of Contents 1 What makes a successful data scientist? PART 1 THE TECH LEAD: CULTIVATING LEADERSHIP 2 Capabilities for leading projects 3 Virtues for leading projects PART 2 THE MANAGER: NURTURING A TEAM 4 Capabilities for leading people 5 Virtues for leading people PART 3 THE DIRECTOR: GOVERNING A FUNCTION 6 Capabilities for leading a function 7 Virtues for leading a function PART 4 THE EXECUTIVE: INSPIRING AN INDUSTRY 8 Capabilities for leading a company 9 Virtues for leading a company PART 5 THE LOOP AND THE FUTURE 10 Landscape, organization, opportunity, and practice 11 Leading in data science and a future outlook
Author: Edward R. Tufte
Publisher:
ISBN: 9780961392116
Category : Computers
Languages : en
Pages : 356
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Book Description
Escaoping flatland. Micro/Macro readings. Layering and separation. Small multiples. Color and information. Narratives of Space and time. Epilogue.
Author: Tennent
Publisher: Pearson Education India
ISBN: 9788177581515
Category :
Languages : en
Pages : 108
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Book Description
