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Anjali Batra
Principal Data Scientist at OpsMx
accuracy and precision, algorithm, attention, behavior, benchmarking, computer, correlation and dependence, data, decision tree, docking (molecular), intelligence, learning, machine learning, magnetic resonance imaging, matrix (mathematics), memory, prediction, software , statistical classification, statistics, time, time series, unsupervised learning
Laura Holliday
Marketing Expert at Depop
advertising, amazon (company), analytics, billionaire, customer relationship management, decision tree, documentary, doula, entrepreneur, entrepreneurship, etsy, expert, facebook, freelancer, fundraising, future, gamification, google, how to, how to be an entrepreneur, how to start a business, innovation, inspiration, investing, leaky bucket, mass media, maternal health, motivation, outsourcing, research, return on investment, san francisco, search engine optimization, silicon valley, silicon valley startups, social media, startup advice, startup business tips, startup company, startup entrepreneurs, startup grind, startup ideas, startup news, startup stories, startup tips, success story, target audience, target market, technology, technology news, unicorn, venture capital, virtual queue
Mathieu Guillame-bert
Research Engineer at Google
#googleio, algorithm, artificial neural network, bird, bit, comma-separated values, competition, concept, decision forest, decision tree, deep learning, design, forest, google, google announcement, google conference, google developer conference, google i/o, google io, insight, keras apis inside tensorflow, learning, library, machine learning, mammal, memory, pixel, pr_pr: google i/o, purpose: educate, question, random forest, random forests, regression analysis, statistical classification, tensorflow, tensorflow at io 2021, tensorflow decision forests, tree-based models, twitter, type: conference talk (full production), youtube
Josh Gordon
Developer Advocate at Google
#googleio, #tfworld, accuracy and precision, ai, algorithm, api, apis, arduino, artificial intelligence, artificial neural network, autocomplete, biology, bird, bit, brain, c++, client-side, comma-separated values, command-line interface, competition, compiler, computer vision, concept, control flow, convolutional neural network, cross entropy, curve fitting, debugger, decision forest, decision tree, deep learning, design, file format, forest, google, google ai, google announcement, google conference, google developer conference, google i/o, google io, gradient descent, graphics processing unit, hyperparameter (machine learning), insight, intro to tensorflow 2.0, introduction to tensorflow 2.0, javascript, josh gordon, keras apis inside tensorflow, learning, library, linear regression, long short-term memory, machine learning, mammal, memory, ml, mnist database, nervous system, numpy, o'reilly, o'reilly tensorflow world, pixel, pr_pr: google i/o, prediction, project jupyter, purpose: educate, question, random forest, random forests, regression analysis, santa clara convention center, sentiment analysis, statistical classification, statistics, tensorflow, tensorflow 2.0, tensorflow 2.0 introduction, tensorflow at io 2021, tensorflow decision forests, tensorflow world, tensorflow world 19, tensorflow world 2019, tf world, tf world 19, tf world 2019, tfworld, tfworld 19, tfworld 2019, training, validation, and test sets, tree-based models, twitter, type: conference talk (full production), web browser, world wide web, youtube
Matteo Interlandi
Senior Scientist at Microsoft GSL
abstraction, artificial intelligence, artificial neural network, bird, bit, cancer, compiler, cuda, data science, decision tree, deep learning, diesel engine, engineering, goal, graph (abstract data type), internet, learning, machine learning, metallica, music, neural network, neuroscience, plato, potato, prediction, python, reason, science, science research, scientific computing, scipy2021, software engineering, valuation (finance), word
Saur Saur
Senior Research SDE at Microsoft
abstraction, artificial intelligence, artificial neural network, bird, bit, cancer, compiler, cuda, data science, decision tree, deep learning, diesel engine, engineering, goal, graph (abstract data type), internet, learning, machine learning, metallica, music, neural network, neuroscience, plato, potato, prediction, python, reason, science, science research, scientific computing, scipy2021, software engineering, valuation (finance), word
Yue Li
Assistant Professor at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Joelle Pineau
Associate Professor at McGill University
academic discipline, accuracy and precision, acm 2020, ai, algorithm, arrhythmia, artificial neural network, automation, backpropagation, best practice, bias, birth defect, bit, brain, canada, cardiovascular disease, communication protocol, complexity, computer network, computer science, computer science 2020, computer science event 2020, congenital heart defect, data, data science, data visualization , database, decision tree, deep learning, deep learning 2020, deep reinforcement learning, disease, epilepsy, evaluation, experiment, expert, facebook, functional electrical stimulation, health care, healthcare, heart, hyperparameter (machine learning), hypothesis, internet, joelle pineau, jöelle pineau, kdd2020, learning, logistic regression, machine learning, mathematical optimization, mathematical proof, mcgill university, motivation, neural network, neurostimulation, prediction, protocol (science), reason, regression analysis, reinforcement learning, reproducibility, research, research labs, reward system, science, scientific community, scientific method, scientist, seizure, sensitivity and specificity, simulation, standford university, stanford conference, statistics, supervised learning, support-vector machine, technology, truth, wids artificial intelligence, wids datathon, wids podcast, women in data, women in data science, women in technology, women in technology conference
Yi Yang
Associate Professor of Statistics at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Jian Tang
Assistant Professor at HEC Montreal
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, child, conformational isomerism, congenital heart defect, costco, data, data science, database, decision tree, diffusion, disease, drug discovery, energy, function (mathematics), grand theft auto v, health care, heart, interactive voice response, joint commission, learning, logic, logistic regression, machine learning, mass, molecular dynamics, molecular mass, moon, physics, prediction, price, protein, protein structure, regression analysis, research, sampling (statistics), sensitivity and specificity, space, support-vector machine, truth, weather, weight
David Buckeridge
Professor at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Liming Guo
Research at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
James Brophy
Professor at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Hanh Nguyen
Рsychologist at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Aihua Liu
Psychologist at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Chao Chao Li
E. B. Eddy Professor and Canada Research Chair at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, truth
Ariane Marelli
Professor of Medicine at McGill University
accuracy and precision, algorithm, arrhythmia, automation, bias, birth defect, bit, canada, cardiovascular disease, congenital heart defect, data, database, decision tree, disease, health care, heart, learning, logistic regression, machine learning, prediction, regression analysis, research, sensitivity and specificity, support-vector machine, 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
Walid Habre
Head Anesthesiological Investigations Unit at Université de Genève
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
Mohamed Rehman
Eric Kobren Professor of Applied Health Informatics at The Johns Hopkins University School of Medicine
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Luis Ahumada
ДолжностьDirector Center for Pediatric Data Science and Analytic Methodology at Johns Hopkins All Children's Hospital
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Ali Jalali
Senior Data Scientist at Biofourmis
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Hannah Lonsdale
Clinical Research Associate at The Johns Hopkins University
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Cesar Caraballo-Cordovez
Postdoctoral Associate at Yale University School of Medicine
algorithm, data, decision tree, decision-making, design, euro, eye, eye (cyclone), feature selection, language interpretation, manuscript, money, mortality rate, number, patient, rainforest, tree
Shiwani Mahajan
Postdoctoral Fellow at Yale School of Medicine
algorithm, data, decision tree, decision-making, design, euro, eye, eye (cyclone), feature selection, language interpretation, manuscript, money, mortality rate, number, patient, rainforest, tree
Daisy Massey
Research Assistant at Yale Center for Outcomes Research and Evaluation
algorithm, data, decision tree, decision-making, design, euro, eye, eye (cyclone), feature selection, language interpretation, manuscript, money, mortality rate, number, patient, rainforest, tree
Tom Zahavy
Research Scientist at DeepMind
algorithm, batiste, bias of an estimator, bomb, complexity, conversation, cooking banana, coupling from the past, data, decision tree, decision-making, design, energy, estimator, euro, eye, eye (cyclone), feature selection, function (mathematics), gradient, immokalee, florida, language interpretation, manuscript, markov chain, matrix (mathematics), money, mortality rate, mysticism, number, paper, patient, plumbing, rainforest, rice, shampoo, simulation, space, stationary state, symbol, temperature, time complexity, tree
Uri Shaham
Member of advisory board at Canny AI
algorithm, data, decision tree, decision-making, design, euro, eye, eye (cyclone), feature selection, language interpretation, manuscript, money, mortality rate, number, patient, rainforest, tree
Harlan Krumholz
Harold H. Hines Jr. Professor at Yale University
algorithm, data, decision tree, decision-making, design, euro, eye, eye (cyclone), feature selection, flight, information, interpolation, knowledge, knowledge transfer, language interpretation, long short-term memory, manuscript, memory, mercury (element), money, mortality rate, motel, mother, number, patient, pressure, rainforest, salt lake city, short-term memory, suffolk, tennessee, tree
Soheil Abbasloo
Post Doctoral Fellow at University of Toronto
anime, bengali language, car, cartesian coordinate system, christmas, cyborg, data, data center, decision tree, design, experiment, funeral, internet, learning, machine learning, matter, mining, mysticism, network, network congestion, space, tree, uber, weed, wireless
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