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Aaron Edell
Senior Director of Product Management at Veritone
Choice Hotels, Facebook, Google, Microsoft, Microsoft Excel, Microsoft PowerPoint, NASDAQ, Netflix, PBS, Siri, YouTube, aaron, aaron edell, accuracy number, ai, ai world, allocating storage, artificial intelligence, big data, building, business, cases, celebrities, cloud, cloud computing, codelounge open, companies, conference expo, customers, data, data analysis, database, decide, deployment options, developer, developer experience, easier, emil ass, etc, excel spreadsheet, file, file format, files, format, future, future proof, good job, graymeta, hog features, human, implement, important, increasing, infrastructure, interesting, inverse correlation, jobs, kind, learn, learning, level set, long time, machine, machine learning, make, metadata, model, model training, models, nab, nab 2016, nab cic, networking lunch, news, operating system, oracle, oracle cloud, oracle developers, people, platform, practical, practical ai, practical al, process, products, read, real tine, recognize celebrities, relates, rights database, shutter stock, single place, social media, spent, start thinking, storage, tailored, technology, thinking, time, tne past, training, training data, tyler schulze, usc, usc sca, validate results, validation set, variety, variety problem, velocity, veritone, vhs tape, video, video file, vnab, vnab 2016, volume, volume overtime, wildlife populations, years ago
Matthew R Shay
President and CEO at National Retail Federation
Best Buy, CNBC, Commerce One, Facebook, Google, Intel, Macy's, Medison, National Retail Properties, Nordstrom, Rent the Runway, Terry's, Walmart, YouTube, annual convention, average corporate, capitol hill, change production, coming year, consumer confidence, consumer goods, enormous amount, huge honor, inventory management, long time, machine learning, member companies, minutes talking, past couple, raise prices, record straight, retail job, retailers areset, search committee, southern border, supreme court, taking place, tax rates, tax reform, terry alluded, thanksgiving weekend, trade war, united states, years ago
Marios Michailidis
Data Scientist at H2O.ai
CNN, GitHub, Google, Kaggle, Microsoft Windows, Twitter, algorithm, algorithms, bad thing, basic idea, bay area, binary classification, blog post, cagle, competitions, computer science, cross validation, data, data science, data scientist, data set, data table, decision trees, deep learning, exciting, experience, factorization machines, faster option, favorite tools, feature, feature engineering, good, good place, good presentation, hands dirty, image classification, knowledge, learning, linear models, machine learning, main reason, mental pressure, model tuning, nice, performing algorithm, premade script, pretty, pretty bad, pro tip, representation learning, scikit learn, semi random, solve problems, tabular data, target, target encoding, theoretical physics, top questions, validation, validation scheme, ways, years ago
Mathias Müller
Data Scientist at H2O.ai
CNN, GitHub, Google, Kaggle, Microsoft Windows, Twitter, algorithm, algorithms, bad thing, basic idea, bay area, binary classification, blog post, cagle, competitions, computer science, cross validation, data, data science, data scientist, data set, data table, decision trees, deep learning, exciting, experience, factorization machines, faster option, favorite tools, feature, feature engineering, good, good place, good presentation, hands dirty, image classification, knowledge, learning, linear models, machine learning, main reason, mental pressure, model tuning, nice, performing algorithm, premade script, pretty, pretty bad, pro tip, representation learning, scikit learn, semi random, solve problems, tabular data, target, target encoding, theoretical physics, top questions, validation, validation scheme, ways, years ago
Vladimir Iglovikov
Senior Computer Vision Engineer at Level5
GitHub, Google, Kaggle, Microsoft Windows, Twitter, algorithm, algorithms, blog post, cagle, competitions, computer science, cross validation, data, data science, data scientist, data set, deep learning, exciting, experience, good, good place, knowledge, machine learning, main reason, mental pressure, nice, performing algorithm, pretty, solve problems, tabular data, theoretical physics, validation, validation scheme, ways, years ago
Sudalai Rajkumar
Data Scientist at H2O.ai
GitHub, Google, Kaggle, Microsoft Windows, Twitter, algorithm, algorithms, blog post, cagle, competitions, computer science, cross validation, data, data science, data scientist, data set, deep learning, exciting, experience, good, good place, knowledge, machine learning, main reason, mental pressure, nice, performing algorithm, pretty, solve problems, tabular data, theoretical physics, validation, validation scheme, ways, years ago
Bojan Tunguz
Data Scientist at H2O.ai
GitHub, Google, Kaggle, Microsoft Windows, Twitter, algorithm, algorithms, blog post, cagle, competitions, computer science, cross validation, data, data science, data scientist, data set, deep learning, exciting, experience, good, good place, knowledge, machine learning, main reason, mental pressure, nice, performing algorithm, pretty, solve problems, tabular data, theoretical physics, validation, validation scheme, ways, years ago
Dmitry Larko
Senior Data Scientist at H2O.ai
/qubvel/segmentation models, 27th place, 51st epoch, = var, Airbus, ArcMap, CNN, D-Box Technologies, Facebook, Funimation, GitHub, Google, H2O (software), Intel, Internet Information Services, Kaggle, Liberty Mutual, Microsoft Windows, Nvidia, Twitter, accept nas, adding xl, additional information, air carrier, algorithm, algorithms, america features, bad thing, basic idea, bay area, big positive, binary classification, binary column, binery features, blog post, border_mde cv2, cagle, careful thinking, categorical encoding, categorical features, cateric features, clean data, cluster centers, cluster ids, competitions, computer science, confident predictions, cross validation, data, data science, data scientist, data set, data table, decision trees, deep learning, dmitry larko, domain knowledge, exam boost, examples, exciting, experience, factorization machines, false positives, faster option, favorite tools, feature, feature engineering, feature interactions, feature —, found, good, good features, good idea, good parameters, good place, good presentation, hands dirty, hot encoding, hotc encoding, https, image, image augmentation, image classification, knowledge, leaderboard shake, leak found, learning, lesson learned, linear models, loss function, machine algorithm, machine learning, main reason, marios michailidis, mental pressure, missing values, mission values, model resnet34', model tuning, nar features, ner features, neural nets, nice, nice package, nice tutorial, numeric features, ornoiy features, pairwise differences, part, performing algorithm, premade script, pretty, pretty bad, private part, pro tip, public leaderboard, random crops, representation learning, scikit learn, semi random, ship size, significant, small, solve problems, standard deviation, statistically significant, tabular data, target, target encoding, target transformation, test set, test time, theoretical physics, top questions, train part, train set, training, training set, validation, validation los, validation scheme, validation set, ways, x1 —, years ago, — deviance, • clustering, • encode, • https, • outliers, • select, • slides, • time, • trained
Satya Nitta
Global Head of AI Solutions for Learning at IBM
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
Joshua Starr
CEO at PDK International Family of Associations
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
Maia Sharpley
Founder & CEO at Odonata Ventures
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
Phil Dunn
CIO at Greenwich Public Schools
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
Jon Supovitz
Director at Consortium for Policy Research in Education
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
Chris Rush
Co-Founder and Chief Program Officer at New Classrooms
Apple Inc., Facebook, IBM, IPad, Intel, Medison, Pro Tools, Rite Aid, Twitter, boards, case, children, companies, data shows, decisions, district, districts, english teacher, existing data, good, good afternoon, huge issue, important, intelligent, iyu steinhardt, key thing, learning, long time, making, nyu steinhardt, school, school boards, school district, school system, single student, student, student data, systems, years ago
David Coleman
President & CEO at The College Board
Instagram, McKinsey & Company, american revolution, assessment, called, college, college board, colleges, constitution, david, david coleman, education, fact, fee waivers, fragile communities, good, good idea, high school, interactive constitution, khan academy, kids, low income, people, people believed, president, test, time, true, white house, world, years ago, young people
Jay Samit
Vice Chairman at Deloitte
4th transformation, = solid, @ cleared, Autodesk, Bruno's, Deloitte, Google, IKEA, National Museum of Health and Medicine, Smith & Wesson, Twitter, ad sales, ad spend, artificial intelligence, augmented reality, billion people, chat bois, connecting sources, digital reality, end market, facial recognition, global summit, good parts, intelligent machine, intemet usage, internet usage, killer app, long time, machine learning, parking, passengers stride, peppers ghost, platinum partner, reality, singularity university, virtual reality, years ago, years usa
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