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Show (77)

Vanessa Klotzman

PhD Student at UC Irvine

accuracy and precision, android (operating system), benchmarking, business model, customer engagement, customer experience, deep learning, end user, evaluation, knowledge economy, loyalty business model, machine learning, motivation, observational learning, parameter, personalization, precision and recall, real-time computing, recommender system, research, robust statistics, sales, scalability, spotify, statistical classification

Igor Markov

Research Scientist at Facebook

accuracy and precision, attention, bias, biology, blended learning, central processing unit, computer virus, conway's game of life, data center, death, deep learning, domestication, electrical grid, emerging technologies, energy, engineer, engineering, evolution, facebook, genome editing, global catastrophic risk, hunting, infection, infrastructure, instagram, machine learning, machine translation, memory, misinformation, nature, network security, neural network, nuclear weapon, precision and recall, prejudice, ray kurzweil, reason, reserved word, risk, software , sql, translation, understanding, user interface, virtual reality, wikipedia, word embedding

Robert Herbig

Lead Software Engineer & AI Practice Lead at SEP

accuracy and precision, ai, amazon mechanical turk, best practice, big data, cloud, cloud architechure, complexity, computer file, decision tree learning, f-score, gmail, hyperparameter (machine learning), intelligence, machine learning, memory, ml, narrative, optical character recognition, overfitting, pipeline (computing), precision and recall, prediction, project jupyter, prototype, six feet up, sixfeetup, training, validation, and test sets, version control, virtual, virtual conference, visualization (graphics)

Jordan Thayer

AI Practice Lead at SEP

accuracy and precision, ai, amazon mechanical turk, best practice, big data, cloud, cloud architechure, complexity, computer file, decision tree learning, f-score, gmail, hyperparameter (machine learning), intelligence, machine learning, memory, ml, narrative, optical character recognition, overfitting, pipeline (computing), precision and recall, prediction, project jupyter, prototype, six feet up, sixfeetup, training, validation, and test sets, version control, virtual, virtual conference, visualization (graphics)

Mike Moran

Chief Product Officer at SoloSegment

accuracy and precision, amazon (company), analytics, engineering, f-score, general data protection regulation, google analytics, ground truth, http cookie, machine learning, natural language processing, pattern recognition, personalization, postgresql, precision and recall, predictive analytics, search engine, search engine indexing, search engine optimization, six feet up, sixfeetup, statistical classification, training, validation, and test sets, understanding, web crawler, website

Emma Strubell

Assistant Professor at Carnegie Mellon University

accuracy and precision, alternating current, analog computer, analog-to-digital converter, artificial neural network, carbon footprint, climate impact, cloud computing, convolutional neural network, deep learning, efficient energy use, electrical resistance and conductance, electricity, graphics processing unit, input/output, kilowatt-hour, low-carbon economy, machine learning, moore's law, ohm's law, performance per watt, precision and recall, resistor, sampling (statistics), voltage

Vivienne Sze

Professor at MIT

accuracy and precision, alternating current, alzheimer's disease, analog computer, analog-to-digital converter, artificial neural network, autonomous robot, binary multiplier, carbon footprint, climate impact, cloud computing, computer, computer vision, convolutional neural network, data compression, deep learning, dementia, efficient energy use, electrical resistance and conductance, electricity, graphics processing unit, image segmentation, inertial measurement unit, inertial navigation system, input/output, kilowatt-hour, low-carbon economy, machine learning, moore's law, neural network, ohm's law, parallel computing, parkinson's disease, performance per watt, precision and recall, resistor, robotics, sampling (statistics), self-driving car, smartphone, speech recognition, unmanned aerial vehicle, voltage

Nicolo Fusi

Principal Researcher at Microsoft Research

accuracy and precision, alternating current, analog computer, analog-to-digital converter, artificial neural network, carbon footprint, climate impact, cloud computing, computer vision, convolutional neural network, data science, deep learning, efficient energy use, electrical resistance and conductance, electricity, expert, gaussian process, google search, graphics processing unit, hyperparameter optimization, image segmentation, input/output, kilowatt-hour, logistic regression, low-carbon economy, machine learning, mathematical optimization, moore's law, neural network, normal distribution, ohm's law, performance per watt, precision and recall, prediction, privacy, project jupyter, random forest, recurrent neural network, regression analysis, resistor, sampling (statistics), science, self-driving car, statistical classification, supervised learning, voltage

Diana Marculescu

Professor and Department Chair at The University of Texas at Austin

computer science event 2021, machine learning 2021, accuracy and precision, acm 2020, alternating current, analog computer, analog-to-digital converter, apple inc., application software, artificial intelligence, artificial neural network, association for computing machinery, augmented reality, carbon footprint, climate impact, cloud computing, computer data storage, computer science 2020, computer science 2021, computer science conference 2021, computer science event, computer science event 2020, computer vision, computing, consumption (economics), convolutional neural network, deep learning, diana marculescu, efficient energy use, electric battery, electrical resistance and conductance, electricity, goal, graphics processing unit, home automation, hypothesis, imagenet, input/output, kdd2020, kilowatt-hour, low-carbon economy, machine learning, memory, mobile phone, moore's law, ohm's law, performance per watt, precision and recall, quantization (signal processing), reason, resistor, sampling (statistics), smartphone, smartwatch, software , system on a chip, tensorflow, tinyml foundation, tinyml2021, tinyml2021 keynote, voltage, wearable technology

Philip Rosenfield

Senior Reseach Program Manager at Microsoft

accuracy and precision, alternating current, analog computer, analog-to-digital converter, artificial neural network, carbon footprint, climate impact, cloud computing, convolutional neural network, deep learning, efficient energy use, electrical resistance and conductance, electricity, graphics processing unit, input/output, kilowatt-hour, low-carbon economy, machine learning, moore's law, ohm's law, performance per watt, precision and recall, resistor, sampling (statistics), voltage

Kirsten Gokay

Senior Product Manager at Appen

accuracy and precision, analytics, api, authentication, credit bureau, credit score, data, database, equifax, facebook, facial recognition system, general data protection regulation, internet, ip, machine learning, multi-factor authentication, online and offline, password, precision and recall, recidivism, sim card, speech recognition, virtual assistant, vulnerability (computing), world wide web

Krishna Rastogi

Associate Director at Association of Data Scientists

accuracy and precision, binary data, cluster analysis, coefficient of determination, confidence interval, deep learning, dimensionality reduction, errors and residuals, interquartile range, linear regression, logistic regression, machine learning, mean squared error, outlier, overfitting, p-value, precision and recall, principal component analysis, quantile, quartile, regression analysis, root mean square, sensitivity and specificity, standard deviation, statistical classification

Aishwarya Verma

Associate Data Scientist at Analytics India Magazine

accuracy and precision, binary data, cluster analysis, coefficient of determination, confidence interval, deep learning, dimensionality reduction, errors and residuals, interquartile range, linear regression, logistic regression, machine learning, mean squared error, outlier, overfitting, p-value, precision and recall, principal component analysis, quantile, quartile, regression analysis, root mean square, sensitivity and specificity, standard deviation, statistical classification

Liang Zhang

Global Sales Strategy & Operations at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, apache spark, api, application software, applications at linkedin, array data structure, array data type, art, artificial intelligence tutorial, artificial neural network, assembly language, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), color, common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data conversion, data science tutorial, data type, debugging, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , file system, film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, library (computing), likelihood function, linear combination, linearity, linkedin, literature, loader (computing), logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parameter (computer programming), parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, preprocessor, protein–protein interaction, python (programming language), radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , source lines of code, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, string (computer science), subroutine, summation, supervised learning, support-vector machine, temporal topic localization, tensor, texas, three-dimensional space, training, validation, and test sets, transcription (linguistics), transformer (machine learning model), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Di Wen

Staff Software Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Yijie Dylan Wang

Software Engineering Manager at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, closed captioning, code-division multiple access, codec, coherence (physics), compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, film frame, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, likelihood function, linearity, linkedin, literature, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimodality, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, sms, social networking service, softmax function, space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video search, video search engine, video understanding, weight, youtube

Bharat Jain

Data Scientist at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Nikita Gupta

Senior Applied Research Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), average, baby talk, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, data, data compression, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, energy, engine, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , film frame, finite set, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, nature, navigation, neural network, news, non-local networks and slowfast, nothing, number, object detection, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, weight, youtube

Suhit Sinha

Senior Applied Research Engineer at LinkedIn

Sumit Srivastava

Staff Applied Research Engineer at LinkedIn

Sirjan Kafle

Senior Machine Learning Engineer, Multimedia AI at LinkedIn

Aman Gupta

Senior Machine Learning Scientist at LinkedIn Multimedia AI

Ananth Sankar

Principal Staff Engineer at LinkedIn

before deep learning , artificial intelligence , artificial intelligence tutorial, computer science conference , feed and ads modeling, introduction to multimedia, visio-lingual representations, 3d cnns, accent (sociolinguistics), accuracy and precision, acm 2020 tutorial, acoustic model, action recognition, ads recommendation, advertising, ai, algorithm, angle, apache hadoop, api, application software, applications at linkedin, art, artificial intelligence tutorial, artificial neural network, association for computing machinery, attention, attention (machine learning), automatic summarization, average, baby talk, backpropagation, bag-of-words model, bangalore, beef, before deep learning , bible, bichon frise, black box, cartesian coordinate system, castle, central processing unit, click-through rate, closed captioning, code-division multiple access, codec, coherence (physics), common technologies for feed and ads recommendation, compass, computer, computer graphics, computer performance, computer science tutorial, computer science tutorials, computer vision, computer vision 2020, computing, concept, convolution, convolutional neural network, cosine similarity, cross entropy, data, data compression, data science, data science tutorial, deconvolution, deep learning, deep learning and cnns, deep learnning, deep learnning tutorial, definition, depiction, design, desk, diagram, diamond, digital image processing, dimension, dsgmm and deep cluster-and-aggregate method, dynamic programming, education, email spam, encoding (memory), energy, engine, english language, enzyme kinetics, equation, essay, euclidean vector, experiment, extract, transform, load, feature (machine learning), feature extraction, feature learning, feed recommendation , feedforward neural network, film frame, finite set, four-dimensional space, function (mathematics), gas, gender, gradient, grayscale, hidden markov model, histogram, history, hyperparameter optimization, image embeddings, image representations , image segmentation, image understanding, imagenet, improvements on 3d cnn, improvements on 3d cnns and two-stream, infection, information, information retrieval, input/output, inspection, instagram, intelligence, interface (computing), internet, introduction - feed, ads, search and spam, inverted index, k-means clustering, kdd2020 tutorials, language, language model, learning, lecture-style tutorials, letter case, likelihood function, linear combination, linearity, linkedin, literature, logic, long short-term memory, machine, machine learning, map, markov chain, markov model, mathematical optimization, matrix (mathematics), mean, meme, memory, metric learning for images, metric space, microsoft, mind, mixture model, mobile app, monotonic function, motivation, moving average, mp3, multimedia, multimedia infrastructure, multimedia search, multimodality, multivariate random variable, music, natural language processing, nature, navigation, neural network, neural networks, news, non-local networks and slowfast, nothing, number, object detection, odsc, odsc india, online and offline, optical character recognition, optical flow, optimization for cnns, oracle corporation, parameter, parity bit, phoneme, pixel, plasterwork, podcast, precision and recall, prediction, protein–protein interaction, radio, reason, recommender system, recurrent neural network, research, robust statistics, satya nadella, search algorithm, search engine, search engine indexing, self-supervised learning, self-supervised video embeddings, semantics, sense, signal, similarity learning, simulation, sms, social media, social networking service, softmax function, software , space, spam detection, spamming, spectral density, spectrogram, speech, speech recognition, speech technologies for video understanding, spotify, statistical classification, statistics, streaming media, summation, supervised learning, support-vector machine, temporal topic localization, texas, three-dimensional space, transcription (linguistics), transmission (mechanics), truck, two-stream networks, typing, understanding, unsupervised learning, upload, use case, vanishing gradient problem, variance, vector graphics, vector space, video, video captioning, video classification, video embeddings and networks, video game, video game console, video game live streaming, video representations used in production, video search, video search engine, video understanding, vocabulary, weight, youtube

Emily Webber

ML Specialist at AWS

accuracy and precision, ai, amazon, amazon elastic compute cloud, artificial intelligence, artificial neural network, aws, aws machine learning summit, aws ml summit, backpropagation, cloud computing, cluster analysis, command-line interface, early stopping, entry point, fraud, ground truth, hml304, how machine learning is done, hyperparameter (machine learning), machine learning, mean squared error, open-source software, parameter (computer programming), precision and recall, regression analysis, risk, software framework, software repository, source code, statistics, tensorflow, upload

Lin Liu

Student at Center of Statistical Research, School of Statistics Southwestern University of Finance and Economics, China

accuracy and precision, acm 2020, association for computing machinery, attention, backbone network, binary classification, binary file, cancer, color, computer science 2020, computer science event 2020, coronavirus disease 2019, ct scan, curve, deep learning, disease, evaluation, f-score, health day at kdd2020, kdd2020, learning, lesion, matrix (mathematics), neural network, pneumonia, precision and recall, sensitivity and specificity, statistical classification, statistics, upload, xbox

Mengshuang He

Center of Statistical Research, School of Statistics Southwestern University of Finance and Economics, China at Student

accuracy and precision, acm 2020, association for computing machinery, attention, backbone network, binary classification, binary file, cancer, color, computer science 2020, computer science event 2020, coronavirus disease 2019, ct scan, curve, deep learning, disease, evaluation, f-score, health day at kdd2020, kdd2020, learning, lesion, matrix (mathematics), neural network, pneumonia, precision and recall, sensitivity and specificity, statistical classification, statistics, upload, xbox

Xiaoxue Gao

Graduate Student at Center of Statistical Research, School of Statistics Southwestern University of Finance and Economics, China

accuracy and precision, acm 2020, association for computing machinery, attention, backbone network, binary classification, binary file, cancer, color, computer science 2020, computer science event 2020, coronavirus disease 2019, ct scan, curve, deep learning, disease, evaluation, f-score, health day at kdd2020, kdd2020, learning, lesion, matrix (mathematics), neural network, pneumonia, precision and recall, sensitivity and specificity, statistical classification, statistics, upload, xbox

Bin Liu

Student at Center of Statistical Research, School of Statistics Southwestern University of Finance and Economics, China

Patrick Deziel

Software Engineer at Unisys

algorithm, cluster analysis, computer programming, data science, diy testing api, engineering, experiment, function (mathematics), gradient descent, hyperparameter (machine learning), hypothesis, level up your ml game , machine leanring, machine learning, metadata, ml code, null (sql), outlier, parameter, precision and recall, prediction, prime number, pycon 2021, pycon unated states 2021, pycon us 2021, pytesting, python, python 2021, python community, python software foundation, python talks 2021, python tutorials, python tutorials 2021, random forest, research, science, statistical classification, stochastic process, unicode, why test ml

Mark Rosno

Software Engineer at Unisys

algorithm, cluster analysis, computer programming, data science, diy testing api, engineering, experiment, function (mathematics), gradient descent, hyperparameter (machine learning), hypothesis, level up your ml game , machine leanring, machine learning, metadata, ml code, null (sql), outlier, parameter, precision and recall, prediction, prime number, pycon 2021, pycon unated states 2021, pycon us 2021, pytesting, python, python 2021, python community, python software foundation, python talks 2021, python tutorials, python tutorials 2021, random forest, research, science, statistical classification, stochastic process, unicode, why test ml