Science Data Booklet

Science Data Booklet
Author: Manjunath.R
Publisher: Manjunath.R
Total Pages: 908
Release: 2020-07-11
Genre: Antiques & Collectibles
ISBN:

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.

Science

Science
Author: Alberta. Alberta Education
Publisher:
Total Pages: 13
Release: 19??
Genre: Chemistry
ISBN:

Chemistry

Chemistry
Author: Alberta. Alberta Education
Publisher:
Total Pages: 11
Release: 1995
Genre: Chemistry
ISBN:

Python Data Science Handbook

Python Data Science Handbook
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
Total Pages: 743
Release: 2016-11-21
Genre: Computers
ISBN: 1491912138

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

Neutron Data Booklet

Neutron Data Booklet
Author: A. J. Dianoux
Publisher: Old City Pub Incorporated
Total Pages: 210
Release: 2003-01-01
Genre: Science
ISBN: 9780970414373

Foundations of Data Science

Foundations of Data Science
Author: Avrim Blum
Publisher: Cambridge University Press
Total Pages: 433
Release: 2020-01-23
Genre: Computers
ISBN: 1108617360

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.

Data Science and Machine Learning

Data Science and Machine Learning
Author: Dirk P. Kroese
Publisher: CRC Press
Total Pages: 538
Release: 2019-11-20
Genre: Business & Economics
ISBN: 1000730778

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