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John Pescatore
Director at SANS
analytics, blockchain, cybersecurity, deep blue (chess computer), deep learning, expert, expert system, information, information security, infosec, internet security, intrusion detection system, machine learning, malware, mind, patch (computing), problem solving, programming language, ransomware, rsa, rsac, rsaconference, search engine, security, signal, siri, software , supervised learning, syslog, vulnerability (computing)
Vinay Prabhu
Chief Scientist at UnifyID
algorithm, amazon (company), angle, angling, applied mathematics, autoencoder, brain, burden of proof (law), cattle, child, child sexual abuse, computer, computer vision, data, datasets, diamond, dimension, ethics, free will, function (mathematics), imagenet, information, kitchen, machine learning, mathematical optimization, mathematics, mind, motivation, muhammad, nearest neighbor search, news, number, password, princeton university, privacy, property, proverb, rape, regression analysis, science, space, speed, stereotype, supervised learning, time, wikipedia
Tianshi Gao
Principal AI Scientist at Cruise
deep learning, electric vehicle, future, gas, google, information, insight, insurance, interest, intersection (road), learning, navigation, prediction, question, reason, risk, self-driving car, species, stop sign, street, supervised learning, technology, traffic, traffic collision, use case
Joseph Ross
Principal Data Scientist at Splunk
category (mathematics), cluster analysis, connected space, continuous function, dimension, equivalence relation, feature selection, field (mathematics), functor, geometry, homology (mathematics), interval (mathematics), k-means clustering, mathematics, metric space, sequence, single-linkage clustering, singular homology, statistical classification, supervised learning, time series, topological space, triangle inequality, unsupervised learning
Harnoor Minhas
Information Technology Team Leader at Quicken Loans
automation, beginner machine learning, beginners, big data, bit, cloud, cloud computing, cloud conference, cluster analysis, computer vision, dimensionality reduction, intelligence, lidar, machine learning, memory, prediction, reinforcement, robot, robotics, self-driving car, six feet up, sixfeetup, statistical classification, supervised learning, tensorflow, training, training, validation, and test sets, trial and error, unsupervised learning, virtual, virtual conference
Robert Neal
Head of Experimentation at LaunchDarkly
action selection, bracket, determinism, function (mathematics), hypertext transfer protocol, language, library, library (computing), motivation, multi-armed bandit, primitive data type, progressive jackpot, python (programming language), reason, reinforcement learning, robot, scala (programming language), sine, slot machine, software framework, state-space representation, supervised learning, trigonometric functions, unsupervised learning, weighted arithmetic mean
Adam Grzywaczewski
Senior Deep Learning Data Scientist at NVIDIA
algorithm, computational resource, computer graphics, computer vision, computing, deep learning, graphics processing unit, hyperparameter optimization, machine learning, natural language processing, neural network, nvidia, perception, reason, recommender system, self-driving car, supercomputer, supervised learning, theory, training, validation, and test sets, translation, unsupervised learning, visual perception
Christian Guttmann
Vice President, Global Head of Artificial Intelligence and Data Science at TietoEVRY
ai, alphago, analytics, artificialintelligence, automation, berlin, board of directors, chatbot, cognitive psychology, conference, consciousness, deeplearning, disruptive innovation, economic growth, employment, entrepreneurship, expert, future, health care, infection, innovation, intelligence, internet of things, intrapreneurship, john mccarthy (computer scientist), ki, künstlicheintelligenz, leadership, learning, machine learning, machinelearning, marvin minsky, medical history, negotiation, performance indicator, proof of concept, psychology, reality, reason, recruitment, riseofai, roai, sales, science, self, social psychology, startup company, strategy, supervised learning, sweden, tourism, turing test, understanding, value proposition, virtual assistant, world economic forum, zukunft
Marcus Gabriel
Machine Ethicist
ai, artificial general intelligence, artificial intelligence, background check, berlin, bias, big data, chinese room, civil society, decision-making, ethics, ethics of artificial intelligence, fabian westerheide, force, information privacy, künstliche intelligenz, law, machine learning, mind, pre-crime, predictive policing, privacy, race (human categorization), reason, research, rights, rise of ai, rise of ai summit, supervised learning, technological singularity, understanding
Hiltrud Dorothea Werner
Member of the Board of Management - Integrity and Legal Affairs at Volkswagen AG
ai, artificial general intelligence, artificial intelligence, background check, berlin, bias, big data, chinese room, civil society, decision-making, ethics, ethics of artificial intelligence, fabian westerheide, force, information privacy, künstliche intelligenz, law, machine learning, mind, pre-crime, predictive policing, privacy, race (human categorization), reason, research, rights, rise of ai, rise of ai summit, supervised learning, technological singularity, understanding
Carla Hustedt
Director at "Centre for Digital Society" bei Stiftung Mercator GmbH
ai, artificial general intelligence, artificial intelligence, background check, berlin, bias, big data, chinese room, civil society, decision-making, ethics, ethics of artificial intelligence, fabian westerheide, force, information privacy, künstliche intelligenz, law, machine learning, mind, pre-crime, predictive policing, privacy, race (human categorization), reason, research, rights, rise of ai, rise of ai summit, supervised learning, technological singularity, understanding
Andreas Dewes
Co-Founder at KIProtect
ai, artificial general intelligence, artificial intelligence, background check, berlin, bias, big data, chinese room, civil society, decision-making, ethics, ethics of artificial intelligence, fabian westerheide, force, information privacy, künstliche intelligenz, law, machine learning, mind, pre-crime, predictive policing, privacy, race (human categorization), reason, research, rights, rise of ai, rise of ai summit, supervised learning, technological singularity, understanding
Peter Seeberg
AI moderator at asimovero.AI
ai, artificial general intelligence, artificial intelligence, background check, berlin, bias, big data, chinese room, civil society, decision-making, ethics, ethics of artificial intelligence, fabian westerheide, force, information privacy, künstliche intelligenz, law, machine learning, mind, pre-crime, predictive policing, privacy, race (human categorization), reason, research, rights, rise of ai, rise of ai summit, supervised learning, technological singularity, understanding
Jingge Zhu
Lecturer (Assistant Professor) at University of Melbourne
algorithm, continuously variable transmission, data, density, double bass, function (mathematics), hypothesis, information, information theory, intuition, learning, machine learning, money, online machine learning, paper, prime number, probability density function, question, risk, semi-supervised learning, supervised learning, tattoo, texas, theorem, wine
Julius von Kügelgen
PhD student at Max Planck Institute for Intelligent Systems, Tübingen Campus
algorithm, causality, cluster analysis, confounding, dependent and independent variables, determinism, disease, expectation–maximization algorithm, experiment, factorization, generative model, information, joint probability distribution, learning, likelihood function, logistic regression, prediction, random variable, regression analysis, semi-supervised learning, signs and symptoms, supervised learning, sympathy, unimodality
Melissa Torgbi
Data Scientist at SAS
air pollution, airplane, alexandria ocasio-cortez, apple inc., atmosphere of earth, carbon, climate, climate model, cluster analysis, computer vision, computing, covid pandemic, deep learning, design, dimensionality reduction, earth, greenhouse gas, health care, human impact on the environment, idea, image segmentation, imagenet, infrastructure, intelligence, knowledge, level of detail (computer graphics), lisa simpson, machine learning, medical image computing, motivation, natural environment, new york city, news, nitrogen, pandemic, pollution, populations of images, prediction, science, self-driving car, severe acute respiratory syndrome coronavirus 2, social media, statistical classification, supervised learning, understanding, unsupervised learning, virus, wind
Kanwal Bhatia
Co-Founder and CSO at MetaLynx
alexandria ocasio-cortez, apple inc., cluster analysis, computer vision, computing, deep learning, dimensionality reduction, health care, idea, image segmentation, imagenet, intelligence, level of detail (computer graphics), machine learning, medical image computing, populations of images, prediction, science, self-driving car, social media, statistical classification, supervised learning, understanding, unsupervised learning
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
Aditya Vetukuri
Software Engineer at Specright
algorithm, application software, chess, chess engine, computer programming, computing, data mining, deep blue (chess computer), deep learning, dimensionality reduction, email, facial expression, frank rosenblatt, garry kasparov, machine learning, perceptron, programming language, recommender system, reinforcement learning, software , supervised learning, training, validation, and test sets, unsupervised learning
Kirti Khade
Associate Consultant at Servian
activation function, analytics, artificial intelligence 2020, data science, data analysis, data science, deep learning, education and research, evaluation, gradient descent, information, language, learning rate, luck, machine learning, matrix (mathematics), neural network, neural networks and deep learning, neural networks machine learning , neural networks tutorial, perception, prediction, sales, science, statistics, supervised learning, supply chain, switch, technology, training, validation, and test sets, web browser, wids mumbai 2020, wids worldwide, woman in data science
Julian Sara Joseph
Senior Full Stack Engineer at Somnoware Healthcare Systems
effective data visualization in the era of covid-19, ai, algorithm, api, artificial intelligence, basic reproduction number, big data, blog, blood donation, blood transfusion, bootstrapping (statistics), constrained optimization, convex function, covid-19, covid-19 data visualization, covid-19 data analysis, covid-19 modelling, covid-19 visualization, data analysis, data science, data science 2020, data science conference 2020, data science in social media, decision tree learning, deep learning, dependent and independent variables, derivative, determinism, differential equation, equation, errors and residuals, estimator, facebook, function (mathematics), gender, genie (feral child), google search, gradient descent, hashtag, hessian matrix, hyperparameter (machine learning), hyperparameter optimization, initial condition, instagram, lasso (statistics), learning, likelihood function, livestreaming, logistic regression, loss function, machine learning, mathematical model, mathematical optimization, music, neural network, news, odds ratio, ordinary differential equation, overfitting, parameter, podcast, privacy, random forest, regression analysis, research, sentiment analysis, sexual orientation, sine, social media, social media analytics, social media analytics python , social media data analytics, social media data analytics tools, social media data analytics tutorial, social media data science, social network, social network analysis, spotify, statistical classification, statistics, supervised learning, twitter, variance, video, whatsapp, wids 2020, wids mumbai 2020, wids worldwide, woman in data science , woman in data science mmmbai , women in ds, women in tech, women in technology, youtube
Madhavi Kaivalya Kandalam
Chief Data Scientist at Loylty Rewards
ai, artificial intelligence, bootstrapping (statistics), constrained optimization, convex function, data science, data science conference 2020, decision tree learning, deep learning, derivative, determinism, errors and residuals, gradient descent, hessian matrix, lasso (statistics), likelihood function, logistic regression, loss function, machine learning, mathematical optimization, neural network, odds ratio, overfitting, random forest, regression analysis, statistical classification, statistics, supervised learning, variance, wids 2020, wids mumbai 2020, wids worldwide, woman in data science , women in tech, women in technology
Aravinda Nanjundappa
Professor at West Virginia University
ai in cardiovascular outcomes, amazon alexa, augmented reality, cardiac stress test, cardiovascular disease, cognitive computing, computer vision, ct scan, deep learning, echocardiography, evidence-based medicine, intelligence, machine learning, magnetic resonance imaging, natural language processing, neural network, problem solving, robotics, self-driving car, simulation, speech recognition, statistical classification, supervised learning, unsupervised learning, watson (computer)
Krishnaswamy Vijay Raghavan
Professor at National Centre for Biological Sciences
ai, algorithm, amazon kindle, applications of artificial intelligence, artificial general intelligence, bias, big data, book, brain, computer science, computing machinery and intelligence, data, database, decision-making, deep learning, determinism, economics, education, empowerment, error, experiment, gross domestic product, history, industry, information, infrastructure, innovation, intelligence, jocelyn bell burnell, key challenges, knowledge, language, learning, machine learning, memory, prediction, resource, statistics, stuart j. russell, supervised learning, technologies, unsupervised learning, user interface
Cees Snoek
Professor in Artificial Intelligence at University of Amsterdam
algorithmic bias, artificial neural network, central processing unit, computer vision, concept, conceptual model, convolutional neural network, data sheet, deep learning, feature learning, hyperparameter optimization, image quality, image segmentation, imagenet, learning to rank, neural network, overfitting, prediction, programmer, representation (arts), statistical classification, supervised learning, support-vector machine, unsupervised learning, variance
Kuan-Chuan Peng
Research Scientist at Mitsubishi Electric Research Laboratories
algorithmic bias, artificial neural network, central processing unit, computer vision, concept, conceptual model, convolutional neural network, data sheet, deep learning, feature learning, hyperparameter optimization, image quality, image segmentation, imagenet, learning to rank, neural network, overfitting, prediction, programmer, representation (arts), statistical classification, supervised learning, support-vector machine, unsupervised learning, variance
Andrew David Bagdanov
Associate Professor at University of Florence
algorithmic bias, artificial neural network, central processing unit, computer vision, concept, conceptual model, convolutional neural network, data sheet, deep learning, feature learning, hyperparameter optimization, image quality, image segmentation, imagenet, learning to rank, neural network, overfitting, prediction, programmer, representation (arts), statistical classification, supervised learning, support-vector machine, unsupervised learning, variance
Leland McInnes
Research Mathematician and Data Scientist at Tutte Institute for Mathematics and Computing
accuracy and precision, algebraic topology, algorithm, artificial intelligence, benchmark (computing), c++, category theory, cluster analysis, clustering high-dimensional data, compact space, compiler, complex number, curse of dimensionality, data science, dataspaces, dimension, dimensionality reduction, distance, euclidean space, facebook, gradient descent, just-in-time compilation, k-nearest neighbors algorithm, logarithm, machine learnin, machine learning, mathematical optimization, mathematics, matrix (mathematics), metric (mathematics), nearest neighbor search, nerve (category theory), numpy, open set, principal component analysis, printer (computing), program optimization, python, python tutorial, science, science research, scientific computing, software engineering, statistical classification, supervised learning, topology, tree (graph theory), visualization (graphics), von neumann architecture
Ramsha Siddiqui
Machine Learning Engineer at Boomtown
api, conditional random field, database, facebook, insurance, internet, learning, machine learning, metadata, multi-label classification, multiclass classification, neural network, sentiment analysis, speech recognition, speech synthesis, statistical classification, supervised learning, tensorflow, training, validation, and test sets, transcription (linguistics), transcription (music), twitter, use case, watson (computer)
Marzyeh Ghassemi
Assistant Professor at University of Toronto
accuracy and precision, active learning, adolescence, adverse event, ai, algorithmic bias, almond, arctic monkeys, artificial intelligence, artificial intelligence in healthcare, artificial neural network, asthma, automation bias, average, bias, bias of an estimator, big data, big data in precision health, brain, bread, bronchitis, child, chronic condition, chronic obstructive pulmonary disease, clinical trial, clinician, computer vision, convolutional neural network, craigslist, data mining, data quality, dialysis, disease, ecology, electronic health record, emergency department, end-of-life care, epidemiology, ethics, experience, expert, fairness (machine learning), false positives and false negatives, fei-fei li, funny people, generative model, gianni versace, gold standard (test), gregory house, hawaii, health, health care, health system, hospital, imagenet, inductive reasoning, informatics, information, informed consent, intelligence, intensive care unit, interdisciplinarity, internal medicine, learning, lexus, logistic regression, long short-term memory, lyme disease, machine learning, marzyeh ghassemi, matrix (mathematics), medical diagnosis, medical privacy, medical record, medicine, mental disorder, mental health, natural language processing, neural network, new york (state), oneonta, new york, palliative care, patient, pediatrics, positive and negative predictive values, precedent, precision health, precision medicine, prediction, privacy, property, radiology, rain, random forest, randomized controlled trial, receiver operating characteristic, recurrent neural network, refrigerant, research, respiratory disease, risk, robotics, science, self-report study, sensitivity and specificity, sepsis, silence, smartphone, stanford, stanford medicine, statistics, subset, supervised learning, surgery, synthetic data, system, technology, temecula, california, toronto, type i and type ii errors, understanding, university of toronto, use case, wheeze, youtube
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