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Expected Goals

Data Modeling for the Sciences: Applications, Basics, Computations

Data Modeling for the Sciences: Applications, Basics, Computations

Optimization for data analysis

The Statistical Physics of Data Assimilation and Machine Learning

Random Matrix Methods for Machine Learning

Educational Data Analytics for Teachers and School Leaders

Think, Do, and Communicate Environmental Science

Data Science for Complex Systems

Text analysis in Python for social scientists: discovery and exploration

An introduction to categorical data analysis

An Introduction to Categorical Data Analysis

Statistical data analytics: foundations for data mining, informatics, and knowledge discovery

Statistical data analytics: foundations for data mining, informatics, and knowledge discovery, solutions manual

Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery, Solutions Manual

Computational Topology for Data Analysis

Data Visualization for Social and Policy Research: A Step-by-Step Approach Using R and Python

A first course in random matrix theory: for physicists, engineers and data scientists

Data mining for business analytics: concepts, techniques, and applications in Microsoft Office Excel with XLMiner

Data mining for business analytics: concepts, techniques, and applications in Microsoft Office Excel with XLMiner

Time Series Data Analysis in Oceanography: Applications Using MATLAB

Modern Dimension Reduction

Images as Data for Social Science Research: An Introduction to Convolutional Neural Nets for Image Classification

Unsupervised Machine Learning for Clustering in Political and Social Research

Sentiment analysis: mining opinions, sentiments, and emotions

The Science of Science

Quantitative Methods of Data Analysis for the Physical Sciences and Engineering

Model-Based Clustering and Classification for Data Science: With Applications in R : 50

Quantitative methods of data analysis for the physical sciences and engineering

Auditing Corporate Surveillance Systems: Research Methods for Greater Transparency

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