Talks

ai, brain, central processing unit, computing, deep learning, graphics processing unit, internet of things, machine learning, machine learning tools, mentorship, ml, research, science, twitter, artificial neural network, convolutional neural network, density, efficient energy use, embedded system, mathematical optimization, matrix (mathematics), matrix multiplication, program optimization, sparse matrix, theory, vector space, watt, sparse networks, kernel (linear algebra), machine learning platform, numenta

data science, gradient descent, math, optimism, statistics, artificial neural network, attention, autoencoder, generative model, least squares, prior probability, race (human categorization), regression analysis, regularization (mathematics), stochastic gradient descent, theory, training, validation, and test sets, transpose, variance, eigenvalues and eigenvectors, inverse problem, applied and computational geometry, applied mathematics, simulation and modeling, linear subspace, wavelet, kernel (linear algebra), proximal gradient methods for learning, super-resolution imaging

big data, coin, competition, economics, economy, machine learning, music, music industry, reason, sql, video, data set, data type, feature selection, function (mathematics), hedge fund, inflation, linear regression, macroeconomics, regression analysis, hilbert space, kernel (linear algebra), macroevolution, reproducing kernel hilbert space, simon kuznets