Ciencia de Datos | 🇬🇧 Data Science

Classification based on Topological Data Analysis

Classification based on Topological Data Analysis

Topological Data Analysis (TDA) is an emergent field that aims to discover topological information hidden in a dataset. TDA tools have been commonly used to create filters and topological descriptors to improve Machine Learning (ML) methods. This paper proposes an algorithm that applies TDA directly to multi-class classification problems, even imbalanced datasets, without any further ML stage

Hugging Face datasets

Hugging Face datasets

One-line dataloaders for many public datasets & Efficient data pre-processing

R0: dde004c79ac901067ab1189ea01b8ac7-Data Science: A First Introduction

Data Science: A First Introduction

The book is structured so that learners spend the first four chapters learning how to use the R programming language and Jupyter notebooks to load, wrangle/clean, and visualize data, while answering descriptive and exploratory data analysis questions. The remaining chapters illustrate how to solve four common problems in data science, which are useful for answering predictive and inferential data analysis questions[…]

R0_fe33488e78e8d3bac711f1ffb6ea5a48-Bayesian-Data-Analysis-course

Bayesian Data Analysis: book & course

This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics

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Tidy Modeling with R

This book provides an introduction to how to use our software to create models. We focus on a dialect of R called the tidyverse that is designed to be a better interface for common tasks using R. If you’ve never heard of or used the tidyverse, Chapter 2 provides an introduction. In this book, we demonstrate how the tidyverse can be used to produce high quality models. The tools used to do this are referred to as the tidymodels packages

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Machine Learning from scratch (by Danny Friedman)

This book covers the building blocks of the most common methods in machine learning. This set of methods is like a toolbox for machine learning engineers. Those entering the field of machine learning should feel comfortable with this toolbox so they have the right tool for a variety of tasks.

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Mastering Shiny

This book complements Shiny’s online documentation and is intended to help app authors develop a deeper understanding of Shiny. After reading this book, you’ll be able to write apps that have more customized UI, more maintainable code, and better performance and scalability.

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Disposable Identities are Elemental(s) in IoT

Rob wants to argue that if intent is linked to an incorrect assessment of identity, and thus not central to an ethics of behaviour, then this opens up an actionable set of actors actually at play in the digtial (IoT, 5G, AI) namely: objects (with added connectivity like NFC), machines with built in connectivity, animals & plants (as ecosystems) and humans alike , as they can be treated as entities.

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OpenMined: open source to make privacy-preserving of AI technologies

With OpenMined, an AI model can be governed by multiple owners and trained securely on an unseen, distributed dataset.The mission of the OpenMined community is to create an accessible ecosystem of tools for private, secure, multi-owner governed AI