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Alexander Guldbrandsen
Machine Learning Engineer at Alm.Brand
behavior, car, cash register, chatbot, conversation, copenhagen, customer, customer experience, customer service, divorce, empathy, engineer, experiment, face masks during the covid-19 pandemic, future, information, machine learning, minimum viable product, paralanguage, predictive modelling, risk, safety, self-service
Torben Strand Andersen
UX designer at Alm.Brand
behavior, car, cash register, chatbot, conversation, copenhagen, customer, customer experience, customer service, divorce, empathy, engineer, experiment, face masks during the covid-19 pandemic, future, information, machine learning, minimum viable product, paralanguage, predictive modelling, risk, safety, self-service
Stine Nørgaard Olesen
Scrum Master and AI Trainer at Alm.Brand
behavior, car, cash register, chatbot, conversation, copenhagen, customer, customer experience, customer service, divorce, empathy, engineer, experiment, face masks during the covid-19 pandemic, future, information, machine learning, minimum viable product, paralanguage, predictive modelling, risk, safety, self-service
Allen Hillery
Be Data Lit
adult education, aesthetics, analytics, big data, culture, database, digital marketing, feeling, game balance, learning, literacy, narrative, podcast, predictive modelling, reason, social media, storytelling, the souls of black folk, trigonometry, visual perception, visualization (graphics), web analytics, wikipedia, workforce development, world wide web
Anchal Bhandari
IoT Presales Specialist at PTC
accuracy and precision, analytics, augmented reality, cloud computing, correlation and dependence, dashboard (business), data collection, digital twin, downtime, fraction, gateway (telecommunications), innovation, internet of things, learning, machine learning, microsoft, mobile app, predictive analytics, predictive modelling, real-time computing, regression analysis, research, sensitivity and specificity
Rajan Bansi
Head at RBC InvestEase
advertising, amazon (company), analytics, bank, big data, brand, co-creation, credit, credit card, customer experience, digital identity, economic bubble, emotion, eureka effect, expert, feeling, finance, governance, interest, investment management, investor, knowledge, leadership, learning, loan, machine learning, market (economics), mind, money laundering, online chat, option (finance), organizational culture, pleasure, predictive modelling, privacy, psychology, reason, risk, social media, videotelephony
Joe Perrone
National Head of Business Development - Technology Banking at Macquarie Group
adam briussi, analytics, automation, barry conlon, brand, consumer behaviour, customer experience, data, digital, digital enterprise, digital transformation, entertainment, fragmentation (computing), innovation, insurance, joe perrone, legal liability, machine learning, macquarie, macquarie bank, macquarie group, macquarie technology summit, mergers and acquisitions, news, overhaul, prediction, predictive modelling, quantium, retail, richard white, risk management, single source of truth, startup company, supermarket, supply chain, technology, walmart, wisetech global
Adam Driussi
Co-Founder and CEO at Quantium
adam briussi, analytics, automation, barry conlon, brand, consumer behaviour, customer experience, data, digital, digital enterprise, digital transformation, entertainment, fragmentation (computing), innovation, insurance, joe perrone, legal liability, machine learning, macquarie, macquarie bank, macquarie group, macquarie technology summit, mergers and acquisitions, news, overhaul, prediction, predictive modelling, quantium, retail, richard white, risk management, single source of truth, startup company, supermarket, supply chain, technology, walmart, wisetech global
Barry Conlon
CEO & Founder at Overhaul
adam briussi, analytics, automation, barry conlon, brand, consumer behaviour, customer experience, data, digital, digital enterprise, digital transformation, entertainment, fragmentation (computing), innovation, insurance, joe perrone, legal liability, machine learning, macquarie, macquarie bank, macquarie group, macquarie technology summit, mergers and acquisitions, news, overhaul, prediction, predictive modelling, quantium, retail, richard white, risk management, single source of truth, startup company, supermarket, supply chain, technology, walmart, wisetech global
Richard White
CEO, Founder and software nerd at WiseTech Global
adam briussi, analytics, automation, barry conlon, brand, consumer behaviour, customer experience, data, digital, digital enterprise, digital transformation, entertainment, fragmentation (computing), innovation, insurance, joe perrone, legal liability, machine learning, macquarie, macquarie bank, macquarie group, macquarie technology summit, mergers and acquisitions, news, overhaul, prediction, predictive modelling, quantium, retail, richard white, risk management, single source of truth, startup company, supermarket, supply chain, technology, walmart, wisetech global
Dean Abbott
Chief Data Scientist at SmarterHQ
accuracy and precision, aid, algorithmic bias, analytics, attention, behavior, bias, brand, coefficient of determination, computer, cross entropy, customer lifetime value, data mining, data science, database, decision tree learning, deep learning, devops, dinosaurs, experiment, fall summit, forecasting, formal verification, future, gender, gini coefficient, industry, insight, knime, knime analytics platform, learning, machine learning, mathematical optimization, mean squared error, occam's razor, overfitting, prediction, predictive analytics, predictive modelling, reason, receiver operating characteristic, regression analysis, reproducibility, research, retail, scope (computer science), statistical hypothesis testing, summit, time, training, validation, and test sets, truth
Assel Altayeva
Data Quality Lead, Strategy & Planning at Peabody
administrative data, adolescence, algorithm, autoregressive model, birth control, blockchain, caesarean section, calibration, causality, child development, childbirth, clinical trial, communication protocol, computer network, conversation, cryptocurrency, data science, differential privacy, economic inequality, encryption, epidemiology, ethereum, federated learning, function (mathematics), gaussian function, gestational age, health, hyperparameter optimization, hypothesis, information, information privacy, information security, life expectancy, likelihood function, likelihood-ratio test, liverpool, machine learning, maximum likelihood estimation, mean, mental health, model selection, mother, multimodal systems, multivariate normal distribution, national health service (england), neural network, normal distribution, parameter, poverty, predictive modelling, pregnancy, privacy, privacy-enhancing technologies, public housing in the united kingdom, reason, research, risk, science, sensitivity and specificity, server (computing), social work, society for worldwide interbank financial telecommunication, statistical causality, statistics, substance abuse, teenage pregnancy, time series, tropical medicine, variance, vector autoregression, violence, white noise
Anna Zaremba
Lead Data Scientist at Hunter Labs Tech
adjacency matrix, analogy, autism spectrum, autoregressive model, bit, blockchain, brain, calibration, causality, communication, computer vision, cryptocurrency, data science, deep learning, detecting fake news online, dimensionality reduction, ethereum, fake news, function (mathematics), gaussian function, gender, graph (discrete mathematics), hyperparameter optimization, hypothesis, image segmentation, information, integer programming, likelihood function, likelihood-ratio test, linear programming, mathematical optimization, matrix (mathematics), maximum likelihood estimation, model selection, multimodal systems, multivariate normal distribution, neuroscience, normal distribution, parameter, predictive modelling, research, science, semi-supervised learning, social network, statistical causality, time, time series, trace (linear algebra), vector autoregression, white noise
Alex Gutman
Lead Data Scientist, at 84.51
virtual analytics summit 2020, ai 2020, analogy, analytics, analytics & data science, analytics conference 2020, analytics leadership, concept, data science, data science conference 2020, decision- making process, decision-making, deep learning, facebook, feeling, information, k-nearest neighbors algorithm, knowledge, language, machine learning, mind, nothing, predictive modelling, reality, science, self-driving car, statistical classification, statistics, supervised learning, time, training, validation, and test sets, uc center for business analytics, uncertainty, university of cincinnati
Radhika Kulkarni
Analytics and Artificial Intelligence Advocate for Universities and Organizations at Self-employed
analytics, big data, computer performance, computing, curriculum, data mining, data science, database, distributed computing, forecasting, innovation, integer programming, machine learning, mathematical optimization, policy, prediction, predictive modelling, program optimization, social media, statistics, technology, text mining, understanding
James Lee
Associate Vice Provost for Digital Scholarship at University of Cincinnati
aesthetics, analysis, analytics, appraisal theory, attitude (psychology), conceptual model, data visualization , emotion, evaluation, language, linguistics, machine learning, predictive modelling, qualitative research, research, research question, sensitivity and specificity, sentiment analysis, statistical classification, text mining, understanding, unstructured data, unsupervised learning, visualization (graphics)
Lindsay Nickel
Country Head at mClinica
aesthetics, analysis, analytics, appraisal theory, attitude (psychology), conceptual model, data visualization , emotion, evaluation, language, linguistics, machine learning, predictive modelling, qualitative research, research, research question, sensitivity and specificity, sentiment analysis, statistical classification, text mining, understanding, unstructured data, unsupervised learning, visualization (graphics)
Reid McCreary
Kroger Pickup/Delivery at 84.51˚
analytics, bricks and clicks, consumer behaviour, customer experience, customer retention, decision-making, economics, feature engineering, forecasting, intention, kroger, loyalty business model, machine learning, prediction, predictive modelling, retail, risk, sales, software testing, theory, time, time series, understanding
Dan Shah SEI
Head of Data Science at Janus Health
analytics, bricks and clicks, consumer behaviour, customer experience, customer retention, decision-making, economics, feature engineering, forecasting, intention, kroger, loyalty business model, machine learning, prediction, predictive modelling, retail, risk, sales, software testing, theory, time, time series, understanding
Rob Dodd
Data Scientist at 84.51˚
analytics, bricks and clicks, consumer behaviour, customer experience, customer retention, decision-making, economics, feature engineering, forecasting, intention, kroger, loyalty business model, machine learning, prediction, predictive modelling, retail, risk, sales, software testing, theory, time, time series, understanding
Chenhui Hu
Data Scientist at Microsoft
machine learning, acm 2020, artificial intelligence, artificial neural network, autoregressive integrated moving average, autoregressive model, computer hardware, computer science 2020, computer science event 2020, computer vision, convolutional neural network, correlation and dependence, cross-validation (statistics), data science, data transformation, deep learning, errors and residuals, inventory, kdd2020, kdd2020 tutorials, long short-term memory, machine learning, memory, moving-average model, neural network, prediction, predictive modelling, real-time computing, recurrent neural network, seasonality, time series, training, validation, and test sets, variance
Vanja Paunic
Data Science at Microsoft
machine learning, acm 2020, artificial intelligence, artificial neural network, autoregressive integrated moving average, autoregressive model, computer hardware, computer science 2020, computer science event 2020, computer vision, convolutional neural network, correlation and dependence, cross-validation (statistics), data science, data transformation, deep learning, errors and residuals, inventory, kdd2020, kdd2020 tutorials, long short-term memory, machine learning, memory, moving-average model, neural network, prediction, predictive modelling, real-time computing, recurrent neural network, seasonality, time series, training, validation, and test sets, variance
Rajesh Ranganath
Assistant Professor at NYU Courant Institute of Mathematical Sciences
accuracy and precision, analytics, belief, cancer, causal inference, causality, decision-making, electronic health record, evidence-based medicine, expected value, hard problem of consciousness, hospital medicine, hypothesis, inference, international system of units, loss function, machine learning, predictive modelling, probability, regression analysis, research, science, statistics, trust (social science)
Suchi Saria
Bayesian Health at Founder
accuracy and precision, analytics, belief, big data, blood glucose monitoring, blood sugar level, cancer, causal inference, causality, chronic condition, computer science, decision-making, digital health, disruptive innovation, electronic health record, emerging technologies, epidemiology, evidence-based medicine, expected value, food and drug administration, hard problem of consciousness, health care, health care reform, health system, hospital medicine, hospital readmission, hypothesis, inference, international system of units, loss function, machine learning, medical imaging, mosquito-borne disease, personalization, predictive modelling, probability, public health, regression analysis, research, rofecoxib, science, statistics, strategies and technologies, trust (social science), type 2 diabetes, zika fever
David Kent
Director at Tufts Medical Center
accuracy and precision, analytics, belief, cancer, causal inference, causality, decision-making, electronic health record, evidence-based medicine, expected value, hard problem of consciousness, hospital medicine, hypothesis, inference, international system of units, loss function, machine learning, predictive modelling, probability, regression analysis, research, science, statistics, trust (social science)
Issa Dahabreh
Associate Professor at Harvard T.H. Chan School of Public Health
accuracy and precision, analytics, belief, cancer, causal inference, causality, decision-making, electronic health record, evidence-based medicine, expected value, hard problem of consciousness, hospital medicine, hypothesis, inference, international system of units, loss function, machine learning, predictive modelling, probability, regression analysis, research, science, statistics, trust (social science)
Brittany Casey
Pediatric Hospital Medicine Fellow at Johns Hopkins All Children’s Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Paola Dees
Physician at Johns Hopkins All Children's Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
John Morrison
Assistant Professor of Pediatrics at The Johns Hopkins University School of Medicine
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Nicola Disma
Director of Unit for Research & InnovationConsultant paediatric Anaesthetist at IRCCS Ospedale Pediatrico Giannina Gaslini
analytics, anesthesia, bayesian inference, census, child, decision tree, demography, disability, health care, hospital, information, johns hopkins all children's hospital, learning, machine learning, medical history, music, neurology, patient, pediatrics, perioperative, prediction, predictive modelling, risk, surgery, visual analytics
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