p:***   15

CS229T/STATS231: Statistical Learning Theory
Course by Percy Liang covers a mix of statistics, computational learning theory, and some online learning. Also surveys the state-of-the-art in theoretical understanding of deep learning (not much to cover unfortunately).
yoga  stanford  course  machine-learning  stats  πŸ‘³  lecture-notes  acm  kernels  learning-theory  deep-learning  frontier  init  ground-up  unit  dimensionality  vc-dimension  entropy-like  extrema  moments  online-learning  bandits  p:***  explore-exploit  advanced 
june 2016 by nhaliday

related tags

academia  accretion  acm  acmtariat  advanced  akrasia  algorithms  ankur-moitra  apollonian-dionysian  applications  approximation  arrows  atoms  average-case  aversion  bandits  bayesian  big-picture  books  caltech  chart  checklists  clever-rats  cmu  concentration-of-measure  concept  conceptual-vocab  confluence  convexity-curvature  core-rats  course  cs  curvature  data-science  deep-learning  differential  dimensionality  distribution  draft  duality  elegance  encyclopedic  ends-means  ensembles  entropy-like  estimate  expert-experience  expert  explore-exploit  extrema  fall-2016  finiteness  fourier  frontier  game-theory  gradient-descent  graph-theory  graphical-models  graphs  ground-up  growth  gtd  habit  hashing  hi-order-bits  high-dimension  homogeneity  ideas  impact  init  iterative-methods  kernels  knowledge  latent-variables  learning-theory  lecture-notes  lectures  levers  linear-algebra  linear-programming  linearity  links  list  machine-learning  manifolds  markov  martingale  math.at  math.ca  math.co  math.gn  math  matrix-factorization  measure  meta:math  metabuch  metameta  mihai  mit  model-class  moments  monte-carlo  multi  nibble  nlp  occam  off-convex  online-learning  optimization  org:bleg  org:edu  org:mat  p:whenever  pac  pdf  perturbation  pigeonhole-markov  polynomials  potential  pragmatic  pre-2013  presentation  princeton  prioritizing  probability  problem-solving  procrastination  productivity  quixotic  random-matrices  random-networks  ratty  regularization  reinforcement  roadmap  rounding  s:***  sample-complexity  sanjeev-arora  scholar-pack  sdp  series  skeleton  smoothness  spectral  stanford  stats  stochastic-processes  stress  studying  sublinear  submodular  synthesis  tcs  telos-atelos  the-monster  thinking  tim-roughgarden  toolkit  top-n  topology  track-record  tricki  unit  vc-dimension  video  winter-2017  wire-guided  yoga  πŸŽ“  πŸ‘³  πŸ¦‰ 

Copy this bookmark: