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François Chollet
Artificial Intelligence Researcher at Google
#googleio, abstraction, adolescence, ai researcher, algorithm, android (operating system), api, artificial intelligence, autoencoder, automation, average, boilerplate code, c++, cloud computing, codec, computer, computer programming, computer vision, concept, conceptual model, conjecture, cross entropy, data compression, data model, deep learning, design, distributed computing, email, embedding, experiment, francois chollet, function (mathematics), google, google announcement, google conference, google developer conference, google i/o, google io, graphics processing unit, imagination, ios, javascript, keras, keras vs tensorflow, kullback–leibler divergence, logic, long short-term memory, low level tensorflow, machine learning, machine learning library, mathematical proof, mathematics, matroid, mean, mean squared error, microsoft, mind, ml conference, modern keras, motivation, multi-core processor, music, normal distribution, nothing, perception, physics, piano, pixel, pr_pr: google i/o, probability distribution, purpose: educate, quantization (signal processing), reason, recursion, research, scaledml, scaledml2020, software , standard keras, swift (programming language), switch, system, tax, technical conference, technology, tensorflow, tensorflow 2021, tensorflow and keras, tensorflow code, theorem, truth, type: conference talk (full production), understanding, use case, variance, vector space, what’s new with tensorflow, world wide web, youtube
Martin Görner
Software Engineer at Google
#googleio, activation function, algorithm, alphago, analytics, api, application programming interface, artificial intelligence, artificial neural network, autoencoder, average, boilerplate code, central processing unit, cloud computing, codec, command-line interface, computer, cross entropy, curve, data compression, deepmind, design, email, encoding (memory), entropy (information theory), function (mathematics), google, google announcement, google cloud ml engine, google conference, google developer conference, google i/o, google io, gradient descent, graphics processing unit, histogram, hyperparameter (machine learning), infoq, input/output, javascript, keras, keras vs tensorflow, kullback–leibler divergence, learning, low level tensorflow, machine learning, machine learning library, mean, mean squared error, mode (statistics), modern keras, multi-core processor, music, neural network, neuron, normal distribution, parameter (computer programming), piano, pixel, pr_pr: google i/o, prediction, probability distribution, purpose: educate, python (programming language), qcon, qcon.ai, rail transport modelling, regularization (mathematics), reinforcement, reinforcement learning, sigmoid function, softmax function, standard keras, statistical classification, supervised learning, switch, technology, tensorboard, tensorflow, tensorflow 2021, tensorflow and keras, tensorflow code, training, validation, and test sets, type: conference talk (full production), variance, vector space, visualization (graphics), what’s new with tensorflow
Karl Weinmeister
Manager, Cloud AI Advocacy at Google
accuracy and precision, algorithm, analytics, application programming interface, artificial neural network, attention, automation, autoregressive model, autoscaling, binary file, blog, categorization, cloud computing, cluster analysis, coefficient of determination, command-line interface, computer file, computing, concept, conference call, confidence interval, configuration file, convolutional neural network, cross-validation (statistics), data, data analysis, deployment environment, determinism, devops, expected value, experiment, forecasting, github, hyperparameter (machine learning), infrastructure, inquiry, internet of things, java (programming language), javascript, json, keras, kubernetes , language model, learning, learning rate, library (computing), life-cycle assessment, long short-term memory, machine, machine learning, maintenance (technical), menu, metadata, moving average, open source, optical character recognition, outlier, paper, parameter, parameter (computer programming), parsing, prediction, probability distribution, program optimization, python (programming language), recurrent neural network, regression analysis, representational state transfer, research, scalability, science, seasonality, sentiment analysis, serverless computing, software , software development, software development kit, speech, speech synthesis, statistics, tensorflow, time series, training, validation, and test sets, unstructured data, web browser, workload
Marjan Mazrouei Sebdani
Machine Learning Engineer at Dun & Bradstreet
3d modeling, ai, ai4, ai4 2020, anger, artificial, artificial intelligence, blister, complexity, computer intelligence, data science, dun & bradstreet, emotion, emotion classification, energy, engineer, georgia (country), hospital, information, intelligence, keras, kinetic energy, learning, long short-term memory, machine, machine learning, marjan mazrouei sebdani, mars, mining, ml, motion, natural language processing, nlp, overfitting, playlist, tf–idf, twitter
James Shearin
Senior Manager, Events - RETCON at Ai4
3d modeling, ai, ai experimental methods, ai research, ai4, ai4 2020, algorithm, algorithmia, android (operating system), anger, application programming interface, application software, artificial, artificial intelligence, atrial fibrillation, atrium (heart), big data, blister, blood clot, cardiology, cardioversion, carnegie mellon university, chris courtney, clinical trial, cloud computing, cmu, complexity, computational fluid dynamics, computer intelligence, computer-assisted surgery, correlation and dependence, covid, credibility, credit score in the united states, data science, database, deep learning, devops, dicom, diego oppenheimer, dun & bradstreet, emotion, emotion classification, end user, energy, engineer, experimental methods, explanation, extract, transform, load, forecasting, georgia (country), happy money, health care, health insurance, heart, heuristic, hospital, humana, hypothesis, image segmentation, information, information security, innovation, intelligence, ios, keras, kinetic energy, leadership, learning, library (computing), loan origination, long short-term memory, machine, machine learning, macroeconomics, marjan mazrouei sebdani, mars, mathematics, mean, median, medicaid, medical imaging, mining, ml, mlops, mode (statistics), moe bataineh, motion, motivation, myocardial infarction, natural language processing, new normal, nlp, outlier, overfitting, pitt, playlist, prahlad menon, prediction, predictive analytics, predictive model, predictive modelling, project jupyter, psychological resilience, quantitative research, quantmd, reason, recommender system, recommender systems, regression analysis, risk management, simulation, startup company, statistical classification, stroke, stroke (disease or medical condition), tensorflow, tf–idf, thrombosis, thrombus, transparency (behavior), tricare, truck driver, twitter, university of pittsburgh, upitt, use case, value proposition, visualization (graphics), web application
Pulkit Bhuwalka
Software Engineer at Google
algorithm, calibration, central processing unit, computer, computer hardware, conversation, correlation and dependence, floating-point arithmetic, flood, hardware acceleration, keras, linear map, lstm quantization, machine learning, machine learning models, map, mathematical optimization, memory, model optimization, music, navigation, optimize your models, optimizing ml models, pruning, quantization (signal processing), quantization aware training support in keras, representation theory, software , speech recognition, suite of tools, tensorflow, tensorflow dev summit, tensorflow dev summit 2020, tensorflow developer summit, tensorflow model optimization toolkit, tf, tf dev summit 20, tf dev summit 2020, tf model optimization toolkit, use case, weight
Paige Bailey
Product Manager (TensorFlow) at Google
#asktensorflow, #devshow, #poweredbytf, #tfdevsummit, #tfworld, ai, algorithm, android (operating system), api, application programming interface, application software, artificial intelligence, artificial neural network, blog, book, boolean data type, brennan saeta, browser, c++, central processing unit, cloud computing, coding, coding with tensorflow, colab, colaboratory, colabs, communicating sequential processes, communication, community, compiler, computer file, computer programming, computer vision, control flow, cross-platform software, cuda, data, data compression, data transformation, datasets, deep learning, derivative, dev news, dev show, dev show top 5, developer show, developers, devs, emoji, english language, estimators, euclidean vector, experiment, expert, feature columns, feed forward (control), file format, find new datasets, finding new datasets, firebase, floating-point arithmetic, function (mathematics), gds: yes;, gesture recognition, getting started in tf 2.0, getting started with ml, gif, google, google ai, google chrome, google colab, google developer show, google developers, google summer of code, gpu, gradient, graphics processing unit, hardware acceleration, hashtag, high-level api, how to use callbacks to cancel training, hyperparameter (machine learning), i'm not there, image classification, information, inheritance (object-oriented programming), interpreter (computing), ios, javascript, kaggle, keras, kernel (operating system), language, language model, laptop, laurence moroney, learning, learning to read with tf and keras, library (computing), long short-term memory, machine, machine learning, ml, mnist database, natural language processing, neural network, news, nlp, numpy, nvidia, o'reilly, o'reilly tensorflow world, open-source software, pac-man, paige, paige bailey, painting, parameter, partial derivative, playstation, prebuilt binary, prediction, primitive data type, profiling (computer programming), program optimization, programming language, project jupyter, python, python (programming language), read with keras, read with tensorflow, read with tensorflow and keras, reason, recap, reinforcement learning, research, reserved word, rtx (ray tracing platform), santa clara convention center, savedmodel, saving tensorflow model, server (computing), social media, source lines of code, speech recognition, string (computer science), subroutine, swift for tensorflow, tensorboard, tensorboard in notebooks, tensorflow, tensorflow 2.0, tensorflow 2.0 upgrade, tensorflow build, tensorflow dev summit, tensorflow dev summit 2020, tensorflow dev summit top 5, tensorflow dev summit ‘19, tensorflow developer summit, tensorflow developers, tensorflow estimators, tensorflow gpu, tensorflow project tracker, tensorflow python support, tensorflow swift, tensorflow world, tensorflow world 19, tensorflow world 2019, tf, tf 2.0, tf dev summit, tf dev summit 20, tf dev summit 2020, tf world, tf world 19, tf world 2019, tfds, tfds 2020, tfds20, tfworld, tfworld 19, tfworld 2019, the developer show, the notebook, tomato, tool, top 5, top 5 from the tensorflow dev summit 20, top 5 from the tensorflow dev summit ‘20, top 5 recap, training, validation, and test sets, translation, twitter, type system, ubuntu, usability, using callbacks, using callbacks in training, using gpus in tensorflow, vocabulary, web browser, web page, william shakespeare, world wide web, youtube, zip (file format)
Jing Pan
Sr. Staff Data Scientist/User Experience Researcher at eHealth Inc.
apple inc., artificial neural network, bandwidth (computing), callback (computer programming), central processing unit, communication, dance, databricks, deep learning, design, fuel efficiency, graphics processing unit, health insurance, keras, library, macintosh, matrix (mathematics), medicare (united states), orbit, patch (computing), python (programming language), research, tensorflow, thread (computing), youtube
Wendao Liu
Senior Data Scientist at eHealth Inc.
apple inc., artificial neural network, bandwidth (computing), callback (computer programming), central processing unit, communication, dance, databricks, deep learning, design, fuel efficiency, graphics processing unit, health insurance, keras, library, macintosh, matrix (mathematics), medicare (united states), orbit, patch (computing), python (programming language), research, tensorflow, thread (computing), youtube
Sean Owen
Data Scientist at Databricks
accuracy and precision, amazon sagemaker, analytics, apache spark, array data structure, bottleneck (production), comma-separated values, computer hardware, computer vision, confounding, cross-validation (statistics), data analysis, data visualization , databricks, deep learning, early stopping, facebook, function (mathematics), global positioning system, gradient boosting, graphics processing unit, hyperparameter optimization, imputation (statistics), isolation (database systems), keras, machine learning, mathematical optimization, memory, microservices, microsoft azure, news, overfitting, painting, parallel computing, prediction, predictive analytics, product lifecycle, regression analysis, representational state transfer, research, scala (programming language), scalability, science, sql, statistical classification, statistics, streaming media, tensorflow, user-defined function, wassily kandinsky
Yogesh H. Kulkarni
Principal Architect - CTO Office at Icertis
ai, algorithm, artificial neural network, census, chordal axis transform, circle, computer, convolutional neural network, curve, data science, deep learning, deflection (engineering), design, engineering, equation, geometry, image segmentation, keras, machine learning, mechanical engineering, medial axis transform, midcurvenn, mind, music, neural networks, odsc, odsc india, parametric equation, polygonal chain, straight skeletons, system of linear equations, torus, training, validation, and test sets, usb
Lak Lakshmanan
Head of Data Analytics and AI Solutions at Google Cloud
accuracy and precision, ai, algorithm, android (operating system), apache hive, artificial intelligence, asynchronous i/o, attention, automatic differentiation, automation, big data, bigquery, binary classification, book, business event, business intelligence, cloud bigquery, cloud computing, command-line interface, compiler, compressed sensing, computer, computer data storage, computer programming, computer vision, concept, conference, continuous integration, convolutional neural network, coursera, data loss prevention software, data model, data type, data warehouse, data-flow diagram, database, deep learning, derivative, directory (computing), emerging tech, entrepreneur conference, entry point, explainable artificial intelligence, extract, transform, load, f1 score, facebook, feature engineering, feature engineering in bigquery, feature engineering in tensorflow 2.0, generative model, geographic information system, github, google, google brain, google developers, google knowledge graph, hash function, inverse problem, java (programming language), json, keras, kirkland ml summit, kubernetes , lak lakshmanan, law, learning, machine learning, machine learning developments, machine learning news, machine learning recent developments, machine learning summit, mapreduce, mean squared error, metadata, ml, ml conference, ml summit, motion planning, natural language processing, optical character recognition, optics, pdf, pipeline (computing), prediction, privacy, programmer, project jupyter, raw data, reality, receipt, regression analysis, regularization (mathematics), reinforcement learning, research, robotics, serverless computing, softmax function, software , software development, statistical classification, statistics, system, tensorflow, tensorflow 2.0, tensorflow keras, training, validation, and test sets, using ai, web hosting service, what’s going on in machine learning, world wide web
Laurence Moroney
Staff Developer Advocate at Google
#asktensorflow, #googleio, #tfworld, accelerating expansion of the universe, accuracy and precision, ai, ai developer updates, ai guidebook, air pollution, algorithm, analytics, android (operating system), android profiler, api, application programming interface, application software, architecture, art, artificial neural network, astronomy , attention, autocomplete, autoencoder, best practice, biology, bit, blog, book, brain, browser, calculus, catchphrase, central processing unit, chrome developer, chrome development, chrome os, chrome os google play store, cloud computing, coding with tensorflow, colab, colaboratory, colabs, comma-separated values, command-line interface, communicating sequential processes, communication, community, computational science, computer, computer file, computer vision, computing, coral, creativity, cross entropy, cuda, curve fitting, dark energy, data, data analysis, data compression, data science, data set, data type, database, datasets, debugger, decision trees, deep learning, deployment environment, design, devs, directory (computing), do it yourself, download, early access, economy, education, emoji, engineering, esp8266, estimators, expansion of the universe, experiment, expert, eye, feature columns, file format, find new datasets, finding new datasets, firebase, fishing, function (mathematics), general-purpose input/output, generation, gesture recognition, getting started in tf 2.0, getting started with ml, gif, google, google announcement, google chrome, google colab, google conference, google developer conference, google developers, google features 2021, google i/o, google io, google play, google play services, google search, google updates, googleio, gpu, gradient descent, graphics processing unit, greenstone, ontario, hackathon, hardware acceleration, hashtag, high-level api, how to use callbacks to cancel training, hyperparameter (machine learning), hypertext transfer protocol, i'm not there, image classification, image segmentation, information, inheritance (object-oriented programming), insurance, internet of things, ios, ios profiler, javascript, jeff dean, johannes kepler, kemal el moujahid, keras, kernel (operating system), knowledge, kubernetes , language, laptop, laurence maroney, laurence moroney, learning, library, library (computing), linear regression, linkedin, listing pwas, machine, machine learning, mars, medical imaging, megan kacholia, message passing interface, ml, ml developer updates, ml kit, mnist database, mobile app, named-entity recognition, national energy research scientific computing center, natural language processing, nervous system, neural architecture search, neural network, news, nothing, numpy, nvidia, on-device machine learning, open source, open-source software, ophthalmology, overfitting, pac-man, paige, paige bailey, painting, pensacola, florida, physical cosmology, pixel, planet, playstation, pr_pr: google i/o, prebuilt binary, progressive web app, project jupyter, proxy server, purpose: educate, purpose: inform, pwa, pwas for chrome os google play store, pwas for chromebooks, pwas in the google play store, python, python (programming language), qr code, queueing theory, radiology, raspberry pi, real-time computing, reason, regression analysis, research, reserved word, robotics, rtx (ray tracing platform), runtime system, savedmodel, saving tensorflow model, scientist, screenshot, search algorithm, self-driving car, selfie, server (computing), simulation, social media, software release life cycle, soul, source code, source lines of code, space, spacetime, speech recognition, statistical classification, statistics, structure, tax, technology, tensor, tensorboard, tensorboard in notebooks, tensorflow, tensorflow 2.0, tensorflow 2.0 upgrade, tensorflow build, tensorflow community, tensorflow dev summit ‘19, tensorflow developers, tensorflow estimators, tensorflow forum, tensorflow gpu, tensorflow lite, tensorflow meets, tensorflow project tracker, tensorflow python support, tensorflow world, tensorflow world 19, tensorflow world 2019, tf, tf 2.0, tf dev summit, tf world 19, tflite, tfx, the notebook, tomato, townsville, training, validation, and test sets, translation, trusted web activity, twerking, twitter, type: conference talk (full production), type: event recap, ubuntu, universe, usability, usb, use case, using callbacks, using callbacks in training, using gpus in tensorflow, visual perception, water, web application, web browser, web page, wheel, william shakespeare, world wide web, xcode, youtube, zip (file format)
Josh Dillon
Software Engineer at Google
artificial neural network, chaos theory, data science, deep learning, errors and residuals, gaussian process, generalized linear model, gpus, keras, layers module, likelihood function, linear regression, loss function, machine learning, machine learning developers, machine learning hardware, markov chain, mean squared error, ml data scientists, ml framework, ml libraries, ml research, ml tutorials, monte carlo method, normal distribution, prediction, probabilistic ml models, probabilistic modeling, probability distribution, project jupyter, python library, python ml library, regression analysis, research, standard deviation, statistical inference, statistical model, statistics, tensorflow, tensorflow developer summit 2019, tensorflow probability, tensorflow probability library, tf dev summit 2019, tf probability, tfds, tfp, tpus, uncertainty, variational bayesian methods
André Susano Pinto
Software Engineer at Google
2019 tensor flow hub, algorithm, artificial neural network, bottleneck (production), car, concept, data, data compression, deepmind, eager execution, engineer, file system, hub, keras, language, learning, library (computing), logic, machine learning, machine learning developers, machine learning models, ml framework, ml modules, ml tutorials, mosquito, neural network, open-source software, preset models, rebuilding models, reinforcement learning, research, reusable machine learning, reusable models, software , software repository, source code, tensorflow, tensorflow developer summit 2019, tensorflow hub, tensorflow hub 2019, tensorflow hub updates, tf 2.0, tf dev summit 2019, tf hub, tf hub modules, tfds, transfer learning, video
Gal Oshri
Product Manager at Google
#poweredbytf, #tfdevsummit, accuracy and precision, application programming interface, bit, building ml models, coding, colab, collaborative ml, collaborative ml with tensorboard, command-line interface, correlation and dependence, data, developers, dog, engineer, experiment, gear, github, google, google cloud machine learning, google developers, google drive, heuristic, hyperparameter, hyperparameter (machine learning), image scanner, information, keras, laptop, learning, machine, machine learning, machine learning conference, machine learning experimentation, metric (mathematics), ml, ml experiments, ml framework, ml libraries, ml models, ml research, ml tutorials, mnist database, neural network, notebook, number, overfitting, paper, parameter, project jupyter, reproducibility, research, screenshot, stack (abstract data type), tensor, tensorboard, tensorboard colab, tensorboard dev, tensorflow, tensorflow 2.0, tensorflow 2019, tensorflow apis, tensorflow colab, tensorflow dev summit, tensorflow dev summit '19, tensorflow dev summit 2020, tensorflow dev summit keynote, tensorflow developer summit, tensorflow keras, tensorflow tensorboard, terrorism, tf, tf dev summit, tf dev summit 20, tf dev summit 2020, tfds, tool, twitter
Karmel Allison
Senior Engineering Manager for TensorFlow at Google
2.0, alpha tf 20, application programming interface, building models, categorical variable, cloud computing, computer programming, control flow, data model, eager execution, fault tolerance, graphics processing unit, inheritance (object-oriented programming), introducing tensorflow 2.0, keras, long short-term memory, machine learning, machine learning developers, machine learning keynote, ml framework, ml models, ml platform, ml tutorials, numpy, optimism, python (programming language), research, scalability, scope (computer science), software framework, software release life cycle, tensor flow 2.0, tensor processing unit, tensorflow, tensorflow 2.0, tensorflow 2.0 alpha, tensorflow 2019, tensorflow alpha, tensorflow apis, tensorflow dev summit keynote, tensorflow developer summit 2019, tensorflow keynote 2019, tf dev summit 2019, tfds, tool, usability, utility
Martin Wicke
Software Engineer, Google Brain at Google
2.0, alpha tf 20, application programming interface, building models, categorical variable, cloud computing, computer programming, control flow, data model, eager execution, fault tolerance, graphics processing unit, inheritance (object-oriented programming), introducing tensorflow 2.0, keras, long short-term memory, machine learning, machine learning developers, machine learning keynote, ml framework, ml models, ml platform, ml tutorials, numpy, optimism, python (programming language), research, scalability, scope (computer science), software framework, software release life cycle, tensor flow 2.0, tensor processing unit, tensorflow, tensorflow 2.0, tensorflow 2.0 alpha, tensorflow 2019, tensorflow alpha, tensorflow apis, tensorflow dev summit keynote, tensorflow developer summit 2019, tensorflow keynote 2019, tf dev summit 2019, tfds, tool, usability, utility
Seungjai Min
Master, Head of AI Research at Samsung SDS
amazon web services, analytics, api, automation, big data, cloud computing, computing, database, deep learning, embedded system, forecasting, http cookie, inventory, keras, logistics, machine learning, motivation, parameter (computer programming), samsung sds, scripting language, software framework, supply chain management, tensorflow
Taeyeop Kim
Samsung SDS Assistant Researcher at Samsung SDS
amazon web services, analytics, api, automation, big data, cloud computing, computing, database, deep learning, embedded system, forecasting, http cookie, inventory, keras, logistics, machine learning, motivation, parameter (computer programming), samsung sds, scripting language, software framework, supply chain management, tensorflow
Peter Gazaryan
Solution Architect at Provectus
artificial neural network, backpropagation, canonical correlation, convolutional neural network, cosine similarity, deep learning, digital image processing, dimension, dimensionality reduction, distance, euclidean distance, euclidean space, euclidean vector, graphics processing unit, k-nearest neighbors algorithm, keras, latent semantic analysis, linear map, machine learning, nearest neighbor search, norm (mathematics), numpy, principal component analysis, tensorflow, web search engine
Denis Kamotsky
Principal Engineer at Macy's
artificial neural network, backpropagation, canonical correlation, convolutional neural network, cosine similarity, deep learning, digital image processing, dimension, dimensionality reduction, distance, euclidean distance, euclidean space, euclidean vector, graphics processing unit, k-nearest neighbors algorithm, keras, latent semantic analysis, linear map, machine learning, nearest neighbor search, norm (mathematics), numpy, principal component analysis, tensorflow, web search engine
Nikhil Thorat
Software Engineer at Google
3d computer graphics, apple inc., application programming interface, application software, artificial neural network, changeup, cloud computing, compiler, computer hardware, computer network, computer vision, computing, data compression, deep learning, fastball, github, google brain, google chrome, graphics processing unit, javascript, keras, macbook pro, machine learning, neural network, node.js, open-source software, polynomial, portable network graphics, quadratic function, software , string (computer science), tensorflow, variable (mathematics), video card, visualization (graphics), web application, web browser, webcam, webgl, world wide web
Daniel Smilkov
Software Engineer at Google
3d computer graphics, apple inc., application programming interface, application software, artificial neural network, changeup, cloud computing, compiler, computer hardware, computer network, computer vision, computing, data compression, deep learning, fastball, github, google brain, google chrome, graphics processing unit, javascript, keras, macbook pro, machine learning, neural network, node.js, open-source software, polynomial, portable network graphics, quadratic function, software , string (computer science), tensorflow, variable (mathematics), video card, visualization (graphics), web application, web browser, webcam, webgl, world wide web
Maurice Nsabimana
Statistician at World Bank
amazon web services, analytics, android (operating system), apache hadoop, api, artificial neural network, big data, computer vision, crowdsourcing, deep learning, definition, education, experiment, gross domestic product, keras, language, library (computing), mobile app, prediction, specification (technical standard), statistical classification, tensorflow, use case, world bank
Jiao Wang
Software Engineer at Intel
amazon web services, analytics, android (operating system), apache hadoop, api, artificial neural network, big data, computer vision, crowdsourcing, deep learning, definition, education, experiment, gross domestic product, keras, language, library (computing), mobile app, prediction, specification (technical standard), statistical classification, tensorflow, use case, world bank
Brooke Wenig
Machine Learning Practice Lead at Databricks
analytics, apache spark, big data, data visualization , debugging, deep learning, directed acyclic graph, extract, transform, load, imagenet, imperative programming, keras, machine learning, ml, neural network, numpy, overfitting, python (programming language), random forest, software bug, software framework, statistical classification, tensorflow, training, validation, and test sets, transfer learning
Ali Ghodsi
CEO & Co-founder at Databricks
#apachespark, #sparkaisummit, alan turing, algorithm, amazon (company), amazon web services, analytics, apache hadoop, apache hive, apache maven, apache spark, application programming interface, bell labs, big data, business intelligence, business models for open-source software, claude shannon, client–server model, climate change, cloud computing, computer file, computer programming, conceptual model, conversation, customer experience, dashboard (business), data lake, data lakes, data model, data quality, data science, data warehouse, data warehouses, data warehousing, database, database schema, database transaction, definition, elon musk, end user, engineering, entertainment, evolution, expert system, extract, transform, load, file system, firmware, free software, generation, health care, health technology in the united states, icloud, innovation, intelligence, internet, internet of things, json, keras, lakehouse architecture built, language, machine learning, mainframe computer, microsoft, mind, minicomputer, mutual exclusion, numpy, observation, open-source model, open-source software, open-source-software movement, password, personal computer, poverty, programming language, prototype, qualitative research, real-time computing, reliability engineering, research, retail, richard stallman, science, scikit-learn, silicon valley, software , software bug, software testing, spreadsheet, startup company, statistics, streaming data, streaming media, supply chain, sustainability, sustainable energy, tensorflow, truth, understanding, use case, venture capital, workload, world wide web
Jules Damji
Spark Developer & Community Advocate at Databricks
accuracy and precision, analytics, apache hadoop, apache spark, best, worst and average case, big data, binary search algorithm, computer network, convolutional neural network, data visualization , debugging, deep learning, directed acyclic graph, extract, transform, load, hash table, imagenet, imperative programming, keras, logistic regression, loss function, machine learning, mapreduce, neural network, numpy, overfitting, python (programming language), random forest, receiver operating characteristic, regression analysis, self-driving car, software bug, software framework, speech recognition, statistical classification, statistics, supervised learning, tensorflow, time complexity, time series, training, validation, and test sets, transfer learning, unsupervised learning
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