Data Analysis With Machine Learning For Psychologists

Author : Chandril Ghosh
Publisher : Unknown
Page : 0 pages
File Size : 51,6 Mb
Release : 2022
Category : Electronic
ISBN : 3031146352

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Data Analysis with Machine Learning for Psychologists by Chandril Ghosh Pdf

The power of data drives the digital economy of the 21st century. It has been argued that data is as vital a resource as oil was during the industrial revolution. An upward trend in the number of research publications using machine learning in some of the top journals in combination with an increasing number of academic recruiters within psychology asking for Python knowledge from applicants indicates a growing demand for these skills in the market. While there are plenty of books covering data science, rarely, if ever, books in the market address the need of social science students with no computer science background. They are typically written by engineers or computer scientists for people of their discipline. As a result, often such books are filled with technical jargon and examples irrelevant to psychological studies or projects. In contrast, this book was written by a psychologist in a simple, easy-to-understand way that is brief and accessible. The aim for this book was to make the learning experience on this topic as smooth as possible for psychology students/researchers with no background in programming or data science. Completing this book will also open up an enormous amount of possibilities for quantitative researchers in psychological science, as it will enable them to explore newer types of research questions. .

Author : Hugo Jair Escalante,Sergio Escalera,Isabelle Guyon,Xavier Baró,Yağmur Güçlütürk,Umut Güçlü,Marcel van Gerven
Publisher : Springer
Page : 299 pages
File Size : 48,9 Mb
Release : 2018-11-29
Category : Computers
ISBN : 9783319981314

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Explainable and Interpretable Models in Computer Vision and Machine Learning by Hugo Jair Escalante,Sergio Escalera,Isabelle Guyon,Xavier Baró,Yağmur Güçlütürk,Umut Güçlü,Marcel van Gerven Pdf

This book compiles leading research on the development of explainable and interpretable machine learning methods in the context of computer vision and machine learning. Research progress in computer vision and pattern recognition has led to a variety of modeling techniques with almost human-like performance. Although these models have obtained astounding results, they are limited in their explainability and interpretability: what is the rationale behind the decision made? what in the model structure explains its functioning? Hence, while good performance is a critical required characteristic for learning machines, explainability and interpretability capabilities are needed to take learning machines to the next step to include them in decision support systems involving human supervision. This book, written by leading international researchers, addresses key topics of explainability and interpretability, including the following: · Evaluation and Generalization in Interpretable Machine Learning · Explanation Methods in Deep Learning · Learning Functional Causal Models with Generative Neural Networks · Learning Interpreatable Rules for Multi-Label Classification · Structuring Neural Networks for More Explainable Predictions · Generating Post Hoc Rationales of Deep Visual Classification Decisions · Ensembling Visual Explanations · Explainable Deep Driving by Visualizing Causal Attention · Interdisciplinary Perspective on Algorithmic Job Candidate Search · Multimodal Personality Trait Analysis for Explainable Modeling of Job Interview Decisions · Inherent Explainability Pattern Theory-based Video Event Interpretations

Author : Chandril Ghosh
Publisher : Springer Nature
Page : 169 pages
File Size : 47,5 Mb
Release : 2022-10-17
Category : Psychology
ISBN : 9783031146343

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Data Analysis with Machine Learning for Psychologists by Chandril Ghosh Pdf

The power of data drives the digital economy of the 21st century. It has been argued that data is as vital a resource as oil was during the industrial revolution. An upward trend in the number of research publications using machine learning in some of the top journals in combination with an increasing number of academic recruiters within psychology asking for Python knowledge from applicants indicates a growing demand for these skills in the market. While there are plenty of books covering data science, rarely, if ever, books in the market address the need of social science students with no computer science background. They are typically written by engineers or computer scientists for people of their discipline. As a result, often such books are filled with technical jargon and examples irrelevant to psychological studies or projects. In contrast, this book was written by a psychologist in a simple, easy-to-understand way that is brief and accessible. The aim for this book was to make the learning experience on this topic as smooth as possible for psychology students/researchers with no background in programming or data science. Completing this book will also open up an enormous amount of possibilities for quantitative researchers in psychological science, as it will enable them to explore newer types of research questions.

Author : Christopher M. Rosett,Austin Hagerty
Publisher : Springer Nature
Page : 266 pages
File Size : 42,5 Mb
Release : 2021-06-14
Category : Psychology
ISBN : 9783030676261

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Introducing HR Analytics with Machine Learning by Christopher M. Rosett,Austin Hagerty Pdf

This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.

Author : Scott Tonidandel,Eden B. King,Jose M. Cortina
Publisher : Routledge
Page : 321 pages
File Size : 47,5 Mb
Release : 2015-11-06
Category : Psychology
ISBN : 9781317702696

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Big Data at Work by Scott Tonidandel,Eden B. King,Jose M. Cortina Pdf

The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.

Author : Mamta Mittal,Lalit Mohan Goyal
Publisher : Springer Nature
Page : 310 pages
File Size : 40,8 Mb
Release : 2022-05-20
Category : Technology & Engineering
ISBN : 9789811917240

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Predictive Analytics of Psychological Disorders in Healthcare by Mamta Mittal,Lalit Mohan Goyal Pdf

This book discusses an interdisciplinary field which combines two major domains: healthcare and data analytics. It presents research studies by experts helping to fight discontent, distress, anxiety and unrealized potential by using mathematical models, machine learning, artificial intelligence, etc. and take preventive measures beforehand. Psychological disorders and biological abnormalities are significantly related with the applications of cognitive illnesses which has increased significantly in contemporary years and needs rapid investigation. The research content of this book is helpful for psychological undergraduates, health workers and their trainees, therapists, medical psychologists, and nurses.

Author : Enrique Garcia Ceja
Publisher : CRC Press
Page : 370 pages
File Size : 44,7 Mb
Release : 2021-11-26
Category : Psychology
ISBN : 9781000484250

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Behavior Analysis with Machine Learning Using R by Enrique Garcia Ceja Pdf

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Author : Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi
Publisher : Springer Nature
Page : 262 pages
File Size : 47,6 Mb
Release : 2023-05-18
Category : Psychology
ISBN : 9783031311727

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An Introduction to Artificial Psychology by Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi Pdf

Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software.

Author : Sang Eun Woo,Louis Tay,Robert W. Proctor
Publisher : American Psychological Association (APA)
Page : 0 pages
File Size : 52,5 Mb
Release : 2020
Category : Psychology
ISBN : 1433831678

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Big Data in Psychological Research by Sang Eun Woo,Louis Tay,Robert W. Proctor Pdf

Big Data in Psychological Research provides an overview of big data theory, research design and analysis, collection methods, applications, ethical concerns, best practices, and future research directions for psychologists.

Author : Mike W. L. Cheung,Suzanne Jak
Publisher : Unknown
Page : 80 pages
File Size : 52,9 Mb
Release : 2019-03-11
Category : Big data
ISBN : 0889375518

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Big Data in Psychology by Mike W. L. Cheung,Suzanne Jak Pdf

Big data is becoming more prevalent in psychology and the behavioral sciences, and so are the methodological and statistical issues that arise from its use. Psychologists need to be equipped to deal with these. Big data can be generated in experimental studies where, for example, participants' physiological and psychological responses are tracked over time or where human brain imaging is employed. Observational data from websites such as Facebook, Twitter, and Google is also of increasing interest to psychologists. These sometimes huge data sets, which are often too large for standard computers and can also contain multiple types of data, bring with them challenging questions about data quality and the generalizability of the results as well as which statistical tools are suitable for analyzing them.The contributions in this volume explore these challenges, looking at the potential of applying machine learning techniques to big data in psychology as well as the split/analyze/meta-analyze (SAM) approach, which allows big data to be split up into smaller datasets so they can be analyzed with conventional multivariate techniques on standard computers. The issues of replicability, prediction accuracy, and combining types of data are also investigated.

Author : Kali H. Trzesniewski,M. Brent Donnellan,Richard Eric Lucas
Publisher : American Psychological Association (APA)
Page : 264 pages
File Size : 50,6 Mb
Release : 2011
Category : Psychology
ISBN : UOM:39076002904675

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Secondary Data Analysis by Kali H. Trzesniewski,M. Brent Donnellan,Richard Eric Lucas Pdf

This wide-ranging yet practical book shows how the analysis of secondary data can provide unique opportunities for advancing psychological science. --Book Jacket.

Author : Ronnel B. King,Jiesi Guo,Ching Sing Chai
Publisher : Frontiers Media SA
Page : 170 pages
File Size : 49,6 Mb
Release : 2022-03-09
Category : Science
ISBN : 9782889746323

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What Big Data Can Tell Us About the Psychology of Learning and Teaching by Ronnel B. King,Jiesi Guo,Ching Sing Chai Pdf

Author : Iven van Mechelen
Publisher : Unknown
Page : 394 pages
File Size : 52,7 Mb
Release : 1993
Category : Computers
ISBN : UOM:39015029276329

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Categories and Concepts by Iven van Mechelen Pdf

A book aimed at advanced undergraduates and graduates in cognitive science and artificial intelligence, linguistics, applied mathematics and data analysis.

Author : Tzung-Pei Hong,Leticia Serrano-Estrada,Akrati Saxena,Anupam Biswas
Publisher : Springer Nature
Page : 297 pages
File Size : 52,8 Mb
Release : 2022-09-18
Category : Computers
ISBN : 9783031108693

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Deep Learning for Social Media Data Analytics by Tzung-Pei Hong,Leticia Serrano-Estrada,Akrati Saxena,Anupam Biswas Pdf

This edited book covers ongoing research in both theory and practical applications of using deep learning for social media data. Social networking platforms are overwhelmed by different contents, and their huge amounts of data have enormous potential to influence business, politics, security, planning and other social aspects. Recently, deep learning techniques have had many successful applications in the AI field. The research presented in this book emerges from the conviction that there is still much progress to be made toward exploiting deep learning in the context of social media data analytics. It includes fifteen chapters, organized into four sections that report on original research in network structure analysis, social media text analysis, user behaviour analysis and social media security analysis. This work could serve as a good reference for researchers, as well as a compilation of innovative ideas and solutions for practitioners interested in applying deep learning techniques to social media data analytics.

Author : Rai, Mritunjay,Pandey, Jay Kumar
Publisher : IGI Global
Page : 332 pages
File Size : 44,8 Mb
Release : 2024-02-26
Category : Psychology
ISBN : 9798369319116

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Using Machine Learning to Detect Emotions and Predict Human Psychology by Rai, Mritunjay,Pandey, Jay Kumar Pdf

In the realm of analyzing human emotions through Artificial Intelligence (AI), a myriad of challenges persist. From the intricate nuances of emotional subtleties to the broader concerns of ethical considerations, privacy implications, and the ongoing battle against bias, AI faces a complex landscape when venturing into the understanding of human emotions. These challenges underscore the intricate balance required to navigate the human psyche with accuracy. The book, Using Machine Learning to Detect Emotions and Predict Human Psychology, serves as a guide for innovative solutions in the field of emotion detection through AI. It explores facial expression analysis, where AI decodes real-time emotions through subtle cues such as eyebrow movements and micro-expressions. In speech and voice analysis, the book unveils how AI processes vocal nuances to discern emotions, considering elements like tone, pitch, and language intricacies. Additionally, the power of text analysis is of great importance, revealing how AI extracts emotional tones from diverse textual communications. By weaving these systems together, the book offers a holistic solution to the challenges faced by AI in understanding the complex landscape of human emotions.