Leanpub Header

Skip to main content

Filters

Category: "Data Science"

Books

  1. This reference volume consists of revised, edited, cross-referenced, and thematically organized articles from Software Diagnostics Institute and Software Diagnostics Library (former Crash Dump Analysis blog) written in July 2009 - January 2010. This major revision contains corrections and WinDbg output color highlighting.

  2. Pack YouR Code
    How to create a simple R package based on the so-called S3 classes
    Gaston Sanchez

    Although this book is not a comprehensive text that covers every single aspect about creating R packages, I’ve written it in the spirit of an extended tutorial or guide document with a relatively simple working example.

  3. This book aims to help you get started with handling strings in R. It provides an overview of several resources that you can use for string manipulation. It covers useful functions in packages "base" and "stringr", printing and formatting characters, regular expressions, and other tricks.

  4. Big Data Analytics
    Data Scientist’s Viewpoint
    Shefali Nayak

    The book is designed to walk you through the various stages of a Big Data Analytics project, concepts and possible avenues when working with huge and overwhelming amounts of structured and unstructured data. Please check the bundle options with this book for better deals!

  5. This companion book to "Spreadsheet Adventures: Coloring Fun with Conditional Formatting" contains Excel files with beautiful patterns, ready for you to change and color to your heart's content. The most important part of this companion book is not the book itself – you can read it for free – but those Excel files provided with your purchase!

  6. Getting Started With Statistics
    A Series of Bitesize Guides For Beginners
    Lee Baker

    Getting Started With Statistics is a series of short, snappy books (4 with more coming soon) that will help you get started with statistics and inspire you to take the next steps.Getting Started With Statistics makes no assumptions about your previous experience and is perfect for beginners and those just getting started with analysing data.

  7. AI organizational scalability - a sample data book
    considerations from a survey
    Roberto Lofaro

    A book using a real case of a Jupyter Notebook with the analysis of a survey. An experiment in transitioning to open data and free the approach to report writing done for decades with customers in activities in cultural, organizational, technological change And sharing ideas about the future of corporate uses of Artificial Intelligence

  8. Introdução à Visualização de Dados
    Simone Barbosa and Gabriel Barbosa

    Este livro está em construção e vem sendo elaborado com base nas notas de aula da disciplina Visualização de Informação lecionada no Departamento de Informática da PUC-Rio. Para enviar comentários ou sugestões, entre em contato através do email livro.vis.dados@gmail.com.

  9. Sampling Techniques
    A Comprehensive Overview
    Shefali Nayak

    This is your go-to book for understanding difficult concepts in Sampling Techniques in lucid language. At the end of this book, you will be familiar with the data collection process and the commonly used random and non-random sampling techniques. Please check the bundle options with this book for better deals!

  10. What Just Happened: Descriptive Statistics
    An Explorer’s Guide to Data
    Shefali Nayak

    The book explains the core concepts and terminologies of Descriptive Statistics using real-world examples. The book contains 17 practice problems, 2 quizzes, 36 graphical representations and numerous examples to enable effective learning and understanding of the concepts. Please check the bundle options with this book for better deals!

  11. Understanding Deep Learning
    Application in Rare Event Prediction
    Chitta Ranjan

    "It is like a voyage of discovery, seeking not for new territory but new knowledge. It should appeal to those with a good sense of adventure," Dr. Frederick Sanger. I hope every reader enjoys this voyage in deep learning and find their adventure.

  12. Data Science Bootstrap
    A practical guide to getting organized for your best data science work
    Eric Ma

    Learn about the best practices for getting organized on your data science projects. Tips, tricks, and all of the reasons why they are important, distilled into a short and easily readable guide.

  13. Tidyverse Skills for Data Science in R
    Roger D. Peng, Carrie Wright, Stephanie Hicks, and Shannon Ellis

    Develop insights from data with tidy tools. Import, wrangle, visualize, and model data with the Tidyverse R packages.

  14. Coffee Break Pandas
    74 Pandas Puzzles to Build Your Pandas Data Science Superpower
    Christian Mayer, Lukas Rieger, and Kyrylo Kravets

    The sexiest job in the 21st century? Data Science!Coffee Break Pandas teaches you the new superpower of analyzing and processing data with Python's Pandas framework. If solving puzzles is fun for you, you'll love ❤ this book with 74 brand-new, hand-crafted Pandas puzzles to help you stay relevant in today's marketplace.

  15. Learn Pandas Basics in Weekend
    Learn Pandas in Weekend Part I.
    Hisham El-Amir

    This weekend, we will cover many fundamental operations of the Pandas. Many of the sections will be similar to those in Data Science Essentials if read.