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Mastering Exploratory Analysis with pandas
Author Harish Garg
Explore Python frameworks like pandas, Jupyter notebooks, and Matplotlib to build data pipelines and data visualizationKey FeaturesLearn to set up data analysis pipelines with pandas and Jupyter notebooks Effective techniques for data selection, manipulation, and v....
Release Date 2018/09 -
Author Gebrenegus Ghilagaber , Habshah Midi , Hossein Riazoshams
The first book to discuss robust aspects of nonlinear regression—with applications using R softwareRobust Nonlinear Regression: with Applications using R covers a variety of theories and applications of nonlinear robust regression. It discusses both parts of the cl....
Release Date 2018/08 -
Introduction to Finite Element Analysis and Design, 2nd Edition
Author Ashok V. Kumar , Bhavani V. Sankar , Nam H. Kim
Introduces the basic concepts of FEM in an easy-to-use format so that students and professionals can use the method efficiently and interpret results properlyFinite element method (FEM) is a powerful tool for solving engineering problems both in solid structural me....
Release Date 2018/08 -
Author Alvaro Fuentes
Enhance your data analysis and predictive modeling skills using popular Python toolsKey FeaturesCover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Acce....
Release Date 2018/08 -
Hands-On Ensemble Learning with R
Author Prabhanjan Narayanachar Tattar
Explore powerful R packages to create predictive models using ensemble methodsKey FeaturesImplement machine learning algorithms to build ensemble-efficient models Explore powerful R packages to create predictive models using ensemble methods Learn to build ensemble....
Release Date 2018/07 -
Author Michael Grogan
Python and R are two of the mainstream languages in data science. Fundamentally, Python is a language for programmers, whereas R is a language for statisticians. In a data science context, there is a significant degree of overlap when it comes to the capabilities o....
Release Date 2018/06 -
Mastering Numerical Computing with NumPy
Author Mert Cuhadaroglu , Umit Mert Cakmak
Enhance the power of NumPy and start boosting your scientific computing capabilitiesAbout This BookGrasp all aspects of numerical computing and understand NumPyExplore examples to learn exploratory data analysis (EDA), regression, and clusteringAccess NumPy librari....
Release Date 2018/06 -
Hands-On Data Analysis with NumPy and pandas
Author Curtis Miller
Get to grips with the most popular Python packages that make data analysis possibleAbout This BookExplore the tools you need to become a data analystDiscover practical examples to help you grasp data processing conceptsWalk through hierarchical indexing and groupin....
Release Date 2018/06 -
Author Matthew Harrison , Jake VanderPlas
Why has Python become an essential tool for programmers, engineers, researchers, and data scientists across academia and industry? This programming language is known for its simplicity and beauty, as well as its large ecosystem of domain-specific tools such as NumP....
Release Date 2018/04 -
Business Case Analysis with R: Simulation Tutorials to Support Complex Business Decisions
Author Robert D. Brown III
This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters mo....
Release Date 2018/03 -
Introduction to Machine Learning with R
Author Scott V. Burger
Machine learning is an intimidating subject until you know the fundamentals. If you understand basic coding concepts, this introductory guide will help you gain a solid foundation in machine learning principles. Using the R programming language, you’ll first start ....
Release Date 2018/03 -
Author Joseph Schmuller
Make the most of R’s extensive toolsetR Projects For Dummies offers a unique learn-by-doing approach. You will increase the depth and breadth of your R skillset by completing a wide variety of projects. By using R’s graphics, interactive, and machine learning tools....
Release Date 2018/02 -
Author J.J. Allaire
Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStud....
Release Date 2018/02 -
Interval Finite Element Method with MATLAB
Author Snehashish Chakraverty , Sukanta Nayak
Interval Finite Element Method with MATLAB provides a thorough introduction to an effective way of investigating problems involving uncertainty using computational modeling. The well-known and versatile Finite Element Method (FEM) is combined with the concept of in....
Release Date 2018/01 -
Analyzing Baseball Data with R
Author Jim Albert , Max Marchi
With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in....
Release Date 2018/01 -
Author Giuseppe Ciaburro
Build effective regression models in R to extract valuable insights from real dataAbout This BookImplement different regression analysis techniques to solve common problems in data science - from data exploration to dealing with missing valuesFrom Simple Linear Reg....
Release Date 2018/01 -
Pandas for Everyone: Python Data Analysis, First Edition
Author Daniel Y. Chen
The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtual....
Release Date 2017/12 -
Author John C. Russ , F. Brent Neal
"John Russ is the master of explaining how image processing gets applied to real-world situations. With Brent Neal, he’s done it again in Measuring Shape, this time explaining an expanded toolbox of techniques that includes useful, state-of-the-art methods that can ....
Release Date 2017/12 -
Electronically Scanned Arrays MATLAB® Modeling and Simulation
Author Arik D. Brown
"[Contains] more lengthy mathematical derivations than most {comparable books] … for arrays, provides for a unique, stand-alone mathematical description that can be adopted by anyone trying to communicate the theoretical foundation for their array design…has insigh....
Release Date 2017/12 -
Computational Nanotechnology Using Finite Difference Time Domain
Author Sarhan M. Musa
The Finite Difference Time Domain (FDTD) method is an essential tool in modeling inhomogeneous, anisotropic, and dispersive media with random, multilayered, and periodic fundamental (or device) nanostructures due to its features of extreme flexibility and easy imple....
Release Date 2017/12 -
PySpark Recipes: A Problem-Solution Approach with PySpark2
Author Raju Kumar Mishra
Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your ....
Release Date 2017/12 -
Author V Kishore Ayyadevara , Ruben Oliva Ramos , L. Felipe Martins
Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPyAbout This BookCovers a wide range of data science tasks using SciPy, NumPy, pandas, and matplotlibEffective recipes on advanced scientific computations, st....
Release Date 2017/12 -
Author Omar Trejo Navarro
This step-by-step guide demonstrates how to build simple-to-advanced applications through examples in R using modern tools.About This BookGet a firm hold on the fundamentals of R through practical hands-on examplesGet started with good R programming fundamentals fo....
Release Date 2017/12 -
Author Ajay Ohri
The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and PythonThe first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python ....
Release Date 2017/11 -
Author Brani Vidakovic
Provides a one-stop resource for engineers learning biostatistics using MATLAB® and WinBUGSThrough its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing bio-oriented engineering fields while implementing software packages....
Release Date 2017/11 -
Functional Data Structures in R: Advanced Statistical Programming in R
Author Thomas Mailund
Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-va....
Release Date 2017/11 -
Beginning Julia Programming: For Engineers and Scientists
Author Sandeep Nagar
Get started with Julia for engineering and numerical computing, especially data science, machine learning, and scientific computing applications. This book explains how Julia provides the functionality, ease-of-use and intuitive syntax of R, Python, MATLAB, SAS, or....
Release Date 2017/11 -
Author Sandeep Nagar
Familiarize yourself with MATLAB using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting and working with files, numerical computation formalism, and the pri....
Release Date 2017/11 -
Author Rahul Lakhanpal , Anshul Joshi
Learn Julia language for data science and data analyticsAbout This BookSet up Julia's environment and start building simple programsExplore the technical aspects of Julia and its potential when it comes to speed and data processingWrite efficient and high-quality ....
Release Date 2017/11 -
Meshing, Geometric Modeling and Numerical Simulation 1
Author Paul Louis George , Houman Borouchaki
Triangulations, and more precisely meshes, are at the heart of many problems relating to a wide variety of scientific disciplines, and in particular numerical simulations of all kinds of physical phenomena. In numerical simulations, the functional spaces of approxi....
Release Date 2017/11