Sing Markdown
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Practical Data Science Cookbook, Second Edition
Author: RATNADIP ADHIKARI
language: en
Publisher: Packt Publishing Ltd
Release Date: 2017-06-29
Over 85 recipes to help you complete real-world data science projects in R and Python Key Features [*] Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data [*] Get beyond the theory and implement real-world projects in data science using R and Python [*] Easy-to-follow recipes will help you understand and implement the numerical computing concepts Book DescriptionAs increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don’t. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. What you will learn [*] Learn and understand the installation procedure and environment required for R and Python on various platforms [*] Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python [*] Build a predictive model and an exploratory model [*] Analyze the results of your model and create reports on the acquired data [*] Build various tree-based methods and Build random forest Who this book is for If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.
Probability, Statistics, and Data
This book is a fresh approach to a calculus based, first course in probability and statistics, using R throughout to give a central role to data and simulation. The book introduces probability with Monte Carlo simulation as an essential tool. Simulation makes challenging probability questions quickly accessible and easily understandable. Mathematical approaches are included, using calculus when appropriate, but are always connected to experimental computations. Using R and simulation gives a nuanced understanding of statistical inference. The impact of departure from assumptions in statistical tests is emphasized, quantified using simulations, and demonstrated with real data. The book compares parametric and non-parametric methods through simulation, allowing for a thorough investigation of testing error and power. The text builds R skills from the outset, allowing modern methods of resampling and cross validation to be introduced along with traditional statistical techniques. Fifty-two data sets are included in the complementary R package fosdata. Most of these data sets are from recently published papers, so that you are working with current, real data, which is often large and messy. Two central chapters use powerful tidyverse tools (dplyr, ggplot2, tidyr, stringr) to wrangle data and produce meaningful visualizations. Preliminary versions of the book have been used for five semesters at Saint Louis University, and the majority of the more than 400 exercises have been classroom tested. The exercises in the book have been added to to the free and open online homework system myopenmath (https://www.myopenmath.com/) which may be useful to instructors.
Collins Cobuild Advanced Dictionary of English
Author: Harper Collins Publishers
language: en
Publisher: Gramedia Pustaka Utama
Release Date: 2016-02-17
This dictionary of American English is designed to help learners write and speak accurate and up-to-date English. • Ideal for upper-intermediate and advanced learners of English • Based on the Collins 4.5-billion-word database, the Collins Corpus • Up-to-date coverage of today’s English, with all words and phrases explained in full sentences • Authentic examples from the Collins Corpus show how English is really used • Extensive help with grammar, including plural forms and verb infl ections • Fully illustrated Word Web and Picture Dictionary boxes provide additional information on vocabulary and key concepts • Vocabulary-building features encourage students to improve their accuracy and fl uency: †- Word Partnership notes highlight important collocations †- Thesaurus entries offer synonyms and antonyms for common words †- Usage notes explain different meanings and uses of the word • Supplements on Grammar, Writing, Speaking, Words That Frequently Appear on TOEFL® and TOEIC®, Text Messaging and Emoticons