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Category: "Data Science"

Books

  1. Matrix and Tensor Factorization for Profiling Player Behavior

    Know more about your users with easy-to-implement and interpretable matrix and tensor factorization based representation learning!

  2. Inferência em Ciências e Aprendizagem de Máquina
    Inferência em Ciências e Aprendizagem de Máquina
    Filosofia e aplicações com estatística e probabilidade.
    Felipe Coelho Argolo

    Um texto introdutório à ciência de dados escrito em língua portuguesa.Usa uma base filosófica para alinhar abstrações matemáticas e aplicações com software. Aborda temas elementares e avançados.R, STAN, testes estatísticos, análise multivariada, inferência bayesiana, redes neurais e deep learning. Teorema do Lim. Central, MCMC, Gradient Descent

  3. A spike in the glass
    A spike in the glass
    Philip T Woodhouse

    Snared the 'daydream' while it was a fresh

  4. Data & Excel
    Data & Excel
    Importer og Analyser data i Excel
    Tue Hellstern

    Lær hvordan du kan bruge Excel til at analysere data.Hvordan kan du arbejde med store datamængder i Excel.

  5. Core ML Survival Guide
    Core ML Survival Guide
    More than you ever wanted to know about mlmodel files and the Core ML and Vision APIs
    Matthijs Hollemans

    Core ML is pretty easy to use — except when it doesn’t do what you want. The Core ML Survival Guide is packed with tips and tricks for solving the most common Core ML problems. Updated for iOS 14 and macOS 11.

  6. Data Speaks - Data Stories that Matter

    See how data can help improve your business and the society at large. Understand the basics of Artificial Intelligence

  7. Daily Fantasy Sports with R
    Daily Fantasy Sports with R
    Building an NBA Projection System
    Robert Zamora

    Data analysis is the process of converting data into useful information. This book introduces data analysis applied to NBA daily fantasy sports (DFS) using the R programming language. You will learn how to wrangle and visualize data, build and test prediction models, and collect and import data from web-based sources.

  8. Learn Python With No Programming Experience: Why, How, and When to Use Functions

    "Help! I can't wrap my head around functions. I consistently find myself struggling to implement functions in a practical way." Even if you have no previous programming experience......if you're stuck trying to learn Python......this guide will explain functions to you. You will also learn how to use functions in a practical way.

  9. Machine Learning Pipeline
    Machine Learning Pipeline
    Experience Gain
    Hisham El-Amir

    Hello! Welcome to this guide to machine learning pipeline. If you want to get up-to-speed with some of the most data modeling techniques and gain experience using them to solve challenging problems, this is a good book for you!

  10. Learn By Examples - A Quick Guide to Java Programming for Text Mining and NLP

    Data Science is a growing field. Want to learn the popular java programming language and Stanford NLP to do text mining and Natural Language Processing, this is the book to grab.

  11. Spreadsheet Adventures - Coloring Fun with Conditional Formatting

    The goal of the "Spreadsheet Adventures" series is to show you the friendly and lighthearted side of Excel. In this first book, “Coloring Fun with Conditional Formatting”, you will learn to create intricate patterns and elegant coloring schemes, as well as moving pictures and time-lapse videos.

  12. Graphs Don’t Lie
    Graphs Don’t Lie
    How to Lie with Graphs and Get Away With It…
    Lee Baker

    In this astonishing book, author Lee Baker uncovers how politicians, the press, corporations and other statistical conmen use graphs and charts to deceive their unwitting audience.Written as a layman’s guide to lying, cheating and deceiving with graphs, there’s not a dull page in sight!Discover the exciting world of graphical lies.

  13. Truth, Lies & Statistics
    Truth, Lies & Statistics
    How to Lie with Statistics
    Lee Baker

    In this eye-opening book, author Lee Baker uncovers the key tricks used by statistical hustlers to deceive, hoodwink and dupe the unwary.Written as a layman’s guide to lying, cheating and deceiving with data and statistics, there’s not a dull page in sight!Discover the exciting world of statistical cheating and persuasive misdirection.

  14. Hypothesis-Based Collaborative Filtering
    Hypothesis-Based Collaborative Filtering
    Retrieving Like-Minded Individuals Based on the Comparison of Hypothesized Preferences
    Amancio Bouza

    In this dissertation, we present hypothesis-based collaborative filtering (HCF) to expose individuals to products which best fits their preferences. HCF retrieves like-minded individuals based on the similarity of their hypothesized preferences by means of machine learning algorithms hypothesizing individuals’ preferences.

  15. Learn By Examples - Introduction to Data and Text Mining using DSTK3

    This book equip reader with data and text mining fundamental using DSTK 3. There are examples and explanatiosn are straight to the point. You will be walked through data mining process using DSTK 3.