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Category: "Data Science"

Data Science

  1. Manual Básico de Estatística Médica com a Linguagem R
    Manual Básico de Estatística Médica com a Linguagem R
    Introdução à análise de dados com a linguagem R e o RStudio
    Henrique Alvarenga da Silva

    Manual básico de uso da linguagem estatística R no RStudio.

  2. Ciencia de Datos con R
    Ciencia de Datos con R
    Importa, manipula, transforma, limpia, visualiza y comunica
    Ruben Sanchez Sancho

    Este libro es para ti si quieres aprender a programar en R.Este libro es para ti si quieres analizar datos con R.Usa el mismo material desarrollado como parte del curso en Ciencia de Datos con R de la plataforma Udemy.

  3. Bio/Recursion
    Bio/Recursion
    An Exploration in R
    Shawn T. O'Neil

    Available as PDF+Code Files or on Amazon, Bio/Recursion explores computer science and bioinformatics via examples in the R programming language. Along the way, over 100 color illustrations, 150 code blocks, and dozens of exercises illuminate the text.

  4. Learn Data with Bash Shell
    Learn Data with Bash Shell
    Explore real-world data at the Linux command line
    Scientific Programmer

    Can you build a script to count the number of sequences in a Big data consisting hundred thousands of nucleotide sequences in 30 seconds? You may wonder to know, this wouldn't take more a than a few words in Bash "grep -c "^>" data.fa" ! This book will help you to become an expert in bash and learn to explore real-world large data sets.

  5. Watershed Analysis in GIS: A Spatial Workbook

    A set of exercises for working with water data in ArcGIS, containing mostly new exercises I haven't published elsewhere - still a work in progress. Prior experience in GIS is assumed (see http://coursera.org/learn/gis for my courses that you can audit for free or take for a certificate)

  6. Demystifying Artificial Intelligence
    Demystifying Artificial Intelligence
    Jeffrey Leek and Divya N.

    This book breaks down the mystique around modern artificial intelligence and guides you through the world of self-driving cars, facial recognition, and digital voice assistants.

  7. Extreme Programming in R and Machine Learning

    The next time you look at an matrimonial advertisement in a news paper or a web age, your brain is going to break down the text and give you social insights and understand the direction the society is headed to. Here is your opportunity to learn and experiment not just on text mining but also web parsing. Get your hands dirty now.

  8. Learn By Examples - A Quick Guide To Data Science With Python

    Data science is a growing field. Want to learn the popular python programming language to do data mining, this is the book to grab.

  9. Data Science Solutions
    Data Science Solutions
    Machine Learning, Python, Neo4j, Kaggle, Cloud Platforms
    Manav Sehgal

    Learn to scale your data science projects from comfort of your development laptop to production scale on the Google and Amazon Clouds. Learn Python for Data Science. Setup Google Cloud Datastore, Firebase, and DynamoDB. Use Neo4j and Open Refine in your workflow.

  10. Building Shiny Apps
    Building Shiny Apps
    Web development for R users
    Pablo Maldonado

    Want to quickly build dashboards to get insight from your data, but don't want to spend on expensive software? Do you need a data-driven app that helps your business? Do you have a general interest in web development, but don't know were to start? Shiny can do this and more for you. This book helps you get started to get your work done.

  11. Natural Language Processing For Hackers
    Natural Language Processing For Hackers
    Learn to build awesome apps that can understand people
    George-Bogdan Ivanov

    Understand the whole process of what is Natural Language Processing, not just bits and pieces. Build practical application, with real-world data. Crawl, clean, build models, fine-tune and deploy.

  12. R for Photobiology
    R for Photobiology
    Theory and recipes for common calculations
    Pedro J. Aphalo, T. Matthew Robson, and Titta Kotilainen

    Photobiology is the branch of science that studies the interactions of living organisms with visible and ultraviolet radiation. This book first presents the theory behind calculations related to research in photobiology and describes how to use R as a tool for carrying out these calculations.

  13. Praxisbuch Informationsmanagement
    Praxisbuch Informationsmanagement
    Wissen im Unternehmen teilen. Guter Umgang mit Dokumenten, E-Mails, Aufgaben und Meetings
    Wolf Steinbrecher and Jan Fischbach

    Wir haben nicht zu wenige, sondern zu viele Informationen. Das ist das Neue unseres Zeitalters. Modernes Informationsmanagement hat deshalb als erste Herausforderung: Wie organisieren wir das Vergessen? Server und E-Mail-Fächer quellen über, ToDo-Listen werden immer länger. Eine strukturierte Vorgehensweise, mit diesem Problem umzugehen, gibt es bislang nicht. Die 2. Herausforderung für den Umgang mit Informationen: Wie schaffen wir den Übergang von einer Einzelkämpferkultur zu einer Kooperationskultur? Wer Informationen braucht, hat oft keinen Zugriff darauf. Auch im 21. Jahrhundert organisieren wir die Verwaltung von Dokumenten und Aufgaben oft noch in abgeschotteten Silos. Ein hoher unproduktiver Synchronisationsaufwand in Form interner E-Mails, Telefonaten und Sitzungen ist die Folge. Das Buch schlägt den Übergang zu einem Denken in Vorgängen vor. Daraus ergeben sich Lösungen für beide Fragestellungen. Denn Kern der Wertschöpfung und Weiterentwicklung eines Unternehmens ist das Abschließen von Vorgängen. Organisiert man die Verwaltung von Dokumenten und E-Mails nach dieser Logik, kann man den Zugriff der Teams auf ihre Vorgänge einfach organisieren. Und auch das Aussondern nicht mehr benötigter Dokumente macht keine Umstände mehr.

  14. Design of Experiments and Observational Studies
    Design of Experiments and Observational Studies
    An Introduction to Design, Causal Inference ,and Analysis Using R
    Nathan Taback

    This book teaches you to design, analyze, and draw meaningful conclusions from experiments and observational studies.  Experiments such as A/B testing and observational data obtained by scraping the web, are commonly encountered in data science.  Many examples are also included from the sciences and social sciences.

  15. A Simulation of Cerebellar Cortex
    A Simulation of Cerebellar Cortex
    An MSc project report from 1974
    Romilly Cocking

    A neural network simulation from 1974, based on Marr's Model of Cerebellar Cortex.