Showing results for "vikram garg"
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Mastering Social Media Mining with R
Extract valuable data from your social media sites and make better business decisions using R
2015
EN
Extract valuable data from your social media sites and make better business decisions using RKey FeaturesExplore the social media APIs in R to capture data and tame itEmploy the machine learning capabilities of R to gain optimal business valueA hands-on guide with real-world examples to help you take advantage of the vast opportunities that come with social media dataBook DescriptionWith an increase in the number of users on ...
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Doing Data Science
Straight Talk from the Frontline
2013
EN
Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know.In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share n...
PHP1,636.49
Machine Learning with R
R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning.
2013
EN
Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain...
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A Desktop Quick Reference
2012
EN
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...
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Learning R
A Step-by-Step Function Guide to Data Analysis
2013
EN
Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, youâ??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includ...
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Pandas Cookbook
Recipes for Scientific Computing, Time Series Analysis and Data Visualization using Python
2017
EN
Publisher s Note: A new second edition, updated completely for pandas 1.x with additional chapters, has now been published. This edition from 2017 is outdated and is based on pandas 0.20. Over 95 hands-on recipes to leverage the power of pandas for efficient scientific computation and data analysisKey FeaturesUse the power of pandas 0.20 to solve most complex scientific computing problems with easeLeverage fast, robust data structures in pandas 0.20 to ...
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or Free with Kobo PlusKNIME Essentials
Perform accurate data analysis using the power of KNIME
2013
EN
Perform accurate data analysis using the power of KNIMEKey FeaturesLearn the essentials of KNIME, from importing data to data visualization and reportingUtilize a wide range of data processing solutionsVisualize your final data sets using KNIME's powerful data visualization optionsBook DescriptionKNIME is an open source data analytics, reporting, and integration platform, which allows you to analyze a small or large amount of...
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- Computer Science (R0)
2012
EN
This easy-to-follow textbook introduces the mathematical language, knowledge and problem-solving skills that undergraduates need to study computing. The language is in part qualitative, with concepts such as set, relation, function and recursion/induction; but it is also partly quantitative, with principles of counting and finite probability. Entwined with both are the fundamental notions of logic and their use for representation and proof.Features: teaches finite math as a languag...
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Bayesian Analysis with Python
Unleash the power and flexibility of the Bayesian framework
2016
EN
Unleash the power and flexibility of the Bayesian frameworkKey FeaturesSimplify the Bayes process for solving complex statistical problems using Python;Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises;Learn how and when to use Bayesian analysis in your applications with this guide.Book DescriptionThe purpose of this book is to teach the main...
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or Free with Kobo PlusMATLAB for Machine Learning
Practical examples of regression, clustering and neural networks
2017
EN
Extract patterns and knowledge from your data in easy way using MATLABKey FeaturesGet your first steps into machine learning with the help of this easy-to-follow guideLearn regression, clustering, classification, predictive analytics, artificial neural networks and more with MATLABUnderstand how your data works and identify hidden layers in the data with the power of machine learning.Book DescriptionMATLAB is the language of ...
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or Free with Kobo PlusMastering Machine Learning with R
Advanced prediction, algorithms, and learning methods with R 3.x
2017
EN
Master machine learning techniques with R to deliver insights in complex projectsKey Features\[\*\] Understand and apply machine learning methods using an extensive set of R packages such as XGBOOST\[\*\] Understand the benefits and potential pitfalls of using machine learning methods such as Multi-Class Classification and Unsupervised Learning\[\*\] Implement advanced concepts in machine learning with this example-rich guideBook ...
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or Free with Kobo PlusBuilding a Recommendation System with R
Learn the art of building robust and powerful recommendation engines using R
2015
EN
Learn the art of building robust and powerful recommendation engines using RKey FeaturesBook DescriptionA recommendation system performs extensive data analysis in order to generate suggestions to its users about what might interest them. R has recently become one of the most popular programming languages for the data analysis. Its structure allows you to interactively explore the data and its modules contain the most cutting-edge techniques thanks to ...
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