**kintopp : statistics**
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The MLIF Book — Machine Learning is Fun!

may 2019 by kintopp

Machine Learning is Fun! The Book This book is for anyone who is curious about machine learning and artificial intelligence. via Pocket

books
dev
howto
learn
python
statistics
ml
may 2019 by kintopp

Distant Horizons: Digital Evidence and Literary Change, Underwood

february 2019 by kintopp

Table of Contents via Pocket

analysis
books
dh
distant
literature
statistics
text
february 2019 by kintopp

Geographical Models with Mathematica - 1st Edition

july 2018 by kintopp

Geographical Models with Mathematica provides a fairly comprehensive overview of the types of models necessary for the development of new geographical knowledge, including stochastic models, models for data analysis, for geostatistics, for networks, for dynamic systems, for cellular automata and for multi-agent systems, all discussed in their theoretical context.

books
geo
wolfram
statistics
simulations
july 2018 by kintopp

GitHub - COMHIS/estc: ESTC analytics

may 2018 by kintopp

This is an algorithmic toolkit for R, designed for transparent quantitative analysis of the British Library English Short Title Catalogue (ESTC) data collection. The package is under active, open development; the tools, analysis, and documentation are preliminary and constantly updated. via Pocket

analysis
bibliography
books
datasets
dev
lists
metadata
statistics
uk
may 2018 by kintopp

Towards Data Science

january 2018 by kintopp

Towards Data Science. Sharing concepts, ideas, and codes

algorithm
learn
resources
statistics
ml
january 2018 by kintopp

Excel vs R: A Brief Introduction to R

october 2017 by kintopp

Quantitative research often begins with the humble process of counting. Historical documents are never as plentiful as a historian would wish, but counting words, material objects, court cases, etc. can lead to a better understanding of the sources and the subject under study. via Pocket

excel
learn
statistics
october 2017 by kintopp

Machines Learn and You Can Too

september 2017 by kintopp

It has taken me some time to build up the courage to dig into machine learning. It can be difficult to learn on your own because of the mathematical terminology that is frequently used to teach the concepts. I’m here to give you hope. You can do it. via Pocket

learn
statistics
ml
september 2017 by kintopp

Learn Data Science by nborwankar

september 2017 by kintopp

Who Nitin Borwankar http://twitter.com/nitin - primary developer (Sponsored by Pivotal Inc. and Alpine Data Labs). What A collection of Data Science Learning materials in the form of IPython Notebooks. Associated data sets. via Pocket

analysis
data
learn
python
statistics
september 2017 by kintopp

Narrative Science | Natural Language Generation Technology

may 2017 by kintopp

USAA prides itself on member engagement. Quill helps USAA scale personalization to its members by automating custom narratives through the power of advanced natural language generation. Working with Narrative Science enabled us to go to market very quickly. via Pocket

language
narrative
statistics
tools
may 2017 by kintopp

GitHub - simplenlg/simplenlg: Java API for Natural Language Generation. Originally developed at the University of Aberdeen's Department of Computing Science. This git repo is the official SimpleNLG version.

may 2017 by kintopp

SimpleNLG is a simple Java API designed to facilitate the generation of Natural Language. It was originally developed at the University of Aberdeen's Department of Computing Science. The discussion list for SimpleNLG is on Google Groups. via Pocket

language
statistics
tools
visualization
may 2017 by kintopp

Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing (The Datasaurus Dozen) | Autodesk Research

may 2017 by kintopp

...make both calculations and graphs. Both sorts of output should be studied; each will contribute to understanding. It can be difficult to demonstrate the importance of data visualization. via Pocket

interactive
methodology
publishing
statistics
visualization
may 2017 by kintopp

Network science and statistical techniques for dealing with uncertainties in archaeological datasets

april 2017 by kintopp

This markdown document provides code and detailed examples associated with the Computer Applications and Quantitative Methods in Archaeology Workshop hosted by Matt Peeples and Tom Brughmans on March 13th, 2017 in Atlanta at Georgia State University. via Pocket

metadata
networks
quality
statistics
april 2017 by kintopp

Frascati Manual - OECD

march 2017 by kintopp

The internationally recognised methodology for collecting and using R&D statistics, the OECD's Frascati Manual is an essential tool for statisticians and science and innovation policy makers worldwide. via Pocket

datasets
howto
research
statistics
march 2017 by kintopp

Seeing Theory

march 2017 by kintopp

Seeing Theory is a project designed and created by Daniel Kunin with support from Brown University's Royce Fellowship Program. The goal of the project is to make statistics more accessible to a wider range of students through interactive visualizations. via Pocket

learn
statistics
teach
theory
visualization
march 2017 by kintopp

Top Stories, Nov 14-20: How Bayesian Inference Works; Data Science and Big Data, Explained; Advanced Time Series Prediction

january 2017 by kintopp

How Bayesian Inference Works; Data Science and Big Data, Explained; Trump, Failure of Prediction, and Lessons for Data Scientist; Combining Different Methods to Create Advanced Time Series Prediction; Questions To Ask When Moving Machine Learning From Practice to Production via Pocket

howto
learn
resources
statistics
january 2017 by kintopp

Eigenvectors and Eigenvalues explained visually

november 2016 by kintopp

It turns out that a matrix like $A$, whose entries are positive and whose columns add up to one (try it!), is called a Markov matrix, and it always has $\lambda = 1$ as its largest eigenvalue. That means there's a value of $v_t$ for which $Av_t =\lambda v_t = 1 v_t = v_t$. via Pocket

learn
statistics
vectors
november 2016 by kintopp

A Guide to Bayesian Statistics — Count Bayesie

may 2016 by kintopp

Bayesian statistics is one of my favorite topics on this blog. But, the more I write the harder it is to find everything! I've decided to build this guide the organize these posts. This should make it easier for everyone to learn the basics. via Pocket

learn
statistics
may 2016 by kintopp

How To Get Started With Machine Learning Algorithms in R - Machine Learning Mastery

march 2016 by kintopp

R is the most popular platform for applied machine learning. When you want to get serious with applied machine learning you will find your way into R. It is very powerful because so many machine learning algorithms are provided. via Pocket

algorithm
learn
statistics
ml
march 2016 by kintopp

Setting up RLink for Mathematica

october 2015 by kintopp

RLink is a standard Mathematica package for accessing R functionality from Mathematica. This is a guide on how to set up RLink with arbitrary R installations on various operating systems and various versions of Mathematica. OS X 10.11 El Capitan users, please see this note. via Pocket

statistics
tools
mathematica
october 2015 by kintopp

Visual Business Intelligence – A d3 Version of My Student Performance Dashboard

october 2015 by kintopp

After the completion of my 2012 Dashboard Design Competition, I created my own version of the Student Performance Dashboard based on the same data that the competitors used. via Pocket

statistics
visualization
october 2015 by kintopp

NBA player career projections | FlowingData

october 2015 by kintopp

As the NBA basketball season gets started, FiveThirtyEight has their player projections for how much each will contribute to their team not just this year but in future seasons. The system is called CARMELO. via Pocket

cofk
history
oxford
statistics
visualization
october 2015 by kintopp

stylo R package - computational stylistics

september 2015 by kintopp

The suite of stylometric tools, so far in the form of separate scripts, has been recently ported to a regular R package. Once installed, it provides a number of functions that can be invoked from inside the R console. 3.4. via Pocket

analysis
statistics
stylometry
text
tools
september 2015 by kintopp

Humanities Data in R - Exploring Networks, Geospatial Data, | Taylor Arnold | Springer

august 2015 by kintopp

Arnold and Tilton are a brilliant team, and this highly accessible book will appeal to a wide range of digital humanists. via Pocket

analysis
books
data
datasets
geo
learn
networks
statistics
images
august 2015 by kintopp

Quick start guide to R for Azure Machine Learning Studio

may 2015 by kintopp

Stephen F Elston, Ph.D. Microsoft Azure Machine Learning contains many powerful machine learning and data manipulation modules. The powerful R language has been described as the lingua franca of analytics. via Pocket

learn
microsoft
statistics
ml
may 2015 by kintopp

A Course for Visualization in R, Taking You From Beginner to Advanced

may 2015 by kintopp

It's the fourth year of running memberships on FlowingData (whoa). With at least one tutorial per month since the beginning, I've worked up a pretty good collection, mostly in R. Each tutorial is self-encapsulated. Download the source and follow the steps. via Pocket

howto
learn
statistics
may 2015 by kintopp

R Programming for… by Roger D. Peng [Leanpub PDF/iPad/Kindle]

may 2015 by kintopp

Data science has taken the world by storm. Every field of study and area of business has been affected as people increasingly realize the value of the incredible quantities of data being generated. But to extract value from those data, one needs to be trained in the proper data science skills. via Pocket

books
data
learn
statistics
may 2015 by kintopp

A new interactive interface for learning R online, for free | R-bloggers

april 2015 by kintopp

Using the open-source swirl project and RStudio server, DataCamp has created an exciting new online learning interface. Discover a fun collection of free interactive R tutorials covering basic R functions, the apply-family, base graphics, data structures and much more. www.datacamp. via Pocket

howto
learn
statistics
april 2015 by kintopp

Elements of Data Analytic… by Jeff Leek [Leanpub PDF/iPad/Kindle]

april 2015 by kintopp

Data analysis is at least as much art as it is science. This book is focused on the details of data analysis that sometimes fall through the cracks in traditional statistics classes and textbooks. It is based in part on the authors blog posts, lecture materials, and tutorials such as: via Pocket

analysis
books
datasets
learn
statistics
april 2015 by kintopp

The Winnower | DIY Scientific Publishing

march 2015 by kintopp

Researchers often want to make claims that two or more groups of participants show the same (or close to the same) performance on a task. For example, a psychologist may seek to demonstrate that an effect is equally strong for men and women. via Pocket

howto
statistics
march 2015 by kintopp

From Counting to Multivariable Calculus in 5 minutes! — Count Bayesie

march 2015 by kintopp

I'd like to start out by saying a huge "Thanks!" to all the people who have visited this blog! The comments and feedback I've received have been really amazing! I have a bunch of great new posts on the way! via Pocket

learn
statistics
march 2015 by kintopp

Rabbit: introduction to R (free web book) | R-bloggers

february 2015 by kintopp

Dear R users, all chapters of Rabbit are now online. Rabbit is a free web book (i.e. a manual) about base R. It covers several base topics such as: R installation, R first steps, R data objects, R data import, R functions, R graphics and R statistical base functions. via Pocket

books
learn
statistics
february 2015 by kintopp

Getting Started with OpenRefine

february 2015 by kintopp

This guide is a companion to the Data Preparation for Digital Humanities Research workshop. It is designed to help you begin using OpenRefine to: Download data (authors-people.csv) This dataset was created by the British Library. We thank them for their love of comics. via Pocket

howto
learn
statistics
mathematica
february 2015 by kintopp

District Data Labs - How to Transition from Excel to R

february 2015 by kintopp

In today's increasingly data-driven world, business people are constantly talking about how they want more powerful and flexible analytical tools, but are usually intimidated by the programming knowledge these tools require and the learning curve they must overcome just to be able to reproduce what via Pocket

howto
learn
statistics
february 2015 by kintopp

Bayesian Logical Data Analysis for the Physical Sciences A Comparative Approach with Mathematica® Support | Statistics for physical sciences and engineering | Cambridge University Press

february 2015 by kintopp

Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. via Pocket

books
statistics
mathematica
february 2015 by kintopp

Loading Data and Basic Formatting in R

february 2015 by kintopp

Oftentimes, the bulk of the work that goes into a visualization isn't visual at all. That is, the drawing of shapes and colors can be relatively quick, and you might spend most of your time getting the data in the format that you need (or just getting data in general). via Pocket

learn
statistics
resources
february 2015 by kintopp

Probability: An Introduction with Statistical Applications, second edition

february 2015 by kintopp

Thoroughly updated, Probability: An Introduction with Statistical Applications, Second Edition features a comprehensive exploration of statistical data analysis as an application of probability. via Pocket

books
learn
statistics
mathematica
february 2015 by kintopp

Cinemetrics - Discussion

february 2015 by kintopp

I've just come across an interesting and useful paper intended as an introduction to statistics for medical researchers, but which is clear enough for anyone to understand. It provides some basics on the difference between samples and popualtions, statistics and parameters, and estimation. via Pocket

learn
statistics
resources
february 2015 by kintopp

Naive Bayes I

january 2015 by kintopp

Naive Bayes classifiers, a family of classifiers that are based on the popular Bayes’ probability theorem, are known for creating simple yet well performing models, especially in the fields of document classification and disease prediction. via Pocket

howto
learn
statistics
ml
january 2015 by kintopp

Review: Wainer, Picturing the Uncertain World

december 2014 by kintopp

Picturing the Uncertain World by Howard Wainer is a book about statistics and statistical thinking, aided by visual depictions of data. Each article in the collection starts by stating a question or phenomenon, which is then investigated further using some clever statistics. via Pocket

books
learn
statistics
visualization
december 2014 by kintopp

Datavu: Statistical Modeling vs Machine Learning

december 2014 by kintopp

I have often used the terms Statistical modeling techniques and Machine learning techniques interchangeably but was not sure about the similarities and differences. So I went through few resources and sharing my findings here. via Pocket

debates
statistics
ml
december 2014 by kintopp

szhorvat/IGraphR · GitHub

october 2014 by kintopp

Call igraph with ease from Mathematica through RLink. RLink is available in Mathematica 9 or later. First, make sure that you are using an R installation that has the igraph package. via Pocket

graphs
statistics
mathematica
october 2014 by kintopp

An Introduction to Correspondence Analysis « The Mathematica Journal

september 2014 by kintopp

Cross tabulations (also known as cross tabs, or contingency tables) often arise in data analysis, whenever data can be placed into two distinct sets of categories. via Pocket

statistics
text
analysis
mathematica
september 2014 by kintopp

Onlinekursreporter: Statistics One Woche 1 | TEXperimenTales

september 2012 by kintopp

Nach Absolvierung der Lectures der ersten Woche aus dem auf Coursera angebotenen Online-Statistik-Kurs (Andrew Conway, Princeton) ist es Zeit für ein erstes Zwischenfazit. via Pocket

learn
statistics
september 2012 by kintopp

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