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RBM with DL4J for Deep Learning

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RBM (Restricted Boltzmann Machine) with DL4J (Deep Learning for Java) , code for mathematics and physics

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RBM with DL4J for Deep Learning

  1. 1. RBM with DL4J for Deep Learning ujava.org 10th Deep Learning Workshop 2015-07-25 www.idosi.com CEO 강신동 Shindong KANG (주)지능도시
  2. 2. www.idosi.comujava.org
  3. 3. www.idosi.comspaceapi.org
  4. 4. www.idosi.comDL4J (Deeplearning4j, Deep Learning for Java)
  5. 5. www.idosi.comHopfield Network
  6. 6. www.idosi.comBoltzmann Machine
  7. 7. www.idosi.comRBM (Restricted Boltzmann Machine)
  8. 8. www.idosi.comGibbs Sampling and Contrastive Divergence
  9. 9. www.idosi.comIris Iris setosa Iris virginicaIris versicolor Sepal length (꽃받침) Sepal width Petal length (꽃잎) Petal width
  10. 10. www.idosi.comIris Data set
  11. 11. www.idosi.comRBM code of DL4J
  12. 12. www.idosi.comRBM execution with CUDA
  13. 13. www.idosi.comlayer of DL4J (real neuron layer)
  14. 14. www.idosi.comNeuralNetConfiguration
  15. 15. www.idosi.comNeuralNetConfiguration.Builder
  16. 16. www.idosi.comGaussian function
  17. 17. www.idosi.comVisibleUnit.GAUSSIAN
  18. 18. www.idosi.comy = 1 + e^x
  19. 19. www.idosi.comy = log (x)
  20. 20. www.idosi.comReLU (Rectified Linear Unit)
  21. 21. www.idosi.comSoftplus function
  22. 22. www.idosi.comActivation Functions Graph
  23. 23. www.idosi.comNoisy ReLU & Leaky ReLU
  24. 24. www.idosi.comHiddenUnit.RECTIFIED
  25. 25. www.idosi.comiteration
  26. 26. www.idosi.comiteration
  27. 27. www.idosi.comweightInit
  28. 28. www.idosi.comEnum WeightInit
  29. 29. www.idosi.comUniformDistribution
  30. 30. www.idosi.comMSE (Mean Squared Error)
  31. 31. www.idosi.comRMSE (Root Mean Squared Error)
  32. 32. www.idosi.comEntropy of Thermodynamics 1862 Clausius S = Q/T 1865 Clausius dS = dQ / T
  33. 33. www.idosi.comMicrostates for Boltzmann's Entropy
  34. 34. www.idosi.comBoltzmann's Entropy Equation
  35. 35. www.idosi.comThe change in entropy
  36. 36. www.idosi.comCalculation Entropy for Process
  37. 37. www.idosi.comLogarithm for very big number and very small number
  38. 38. www.idosi.comlogarithm of chemistry pH
  39. 39. www.idosi.comLoss Function
  40. 40. www.idosi.comLoss Function
  41. 41. www.idosi.comMSE's defect
  42. 42. www.idosi.comCross Entropy Error
  43. 43. www.idosi.comRegularization
  44. 44. www.idosi.comL2 coefficient for regularization L2 is used only when regularization(true) L2 is for how much the regularization should count.
  45. 45. www.idosi.comHessian Matrix for BFGS
  46. 46. www.idosi.comBFGS
  47. 47. www.idosi.comLimited-memory BFGS
  48. 48. www.idosi.comMomentum (운동량)
  49. 49. www.idosi.comMomentum in physics
  50. 50. www.idosi.comMomentum in Deep Learning
  51. 51. www.idosi.comMomentum Learning Rule
  52. 52. www.idosi.cominterface Model
  53. 53. www.idosi.cominterface Layer
  54. 54. www.idosi.comLayer.Type
  55. 55. www.idosi.cominterface hierarchy
  56. 56. www.idosi.comLayerFactories
  57. 57. www.idosi.comScoreIterationListener
  58. 58. www.idosi.cominterface Model.fit()
  59. 59. www.idosi.comRBM : Early epochs of training
  60. 60. www.idosi.comRBM : Late epochs of training 7학년일반
  61. 61. www.idosi.comTarget Value & Test Value Target Test T T F F TT TF FT FF Not for RBM (RBM is unsupervised learning)
  62. 62. www.idosi.comPrecision (정확률) Target Test T T F F TT TF FT FF TT TT + FT
  63. 63. www.idosi.comRecall (재현률) Target Test T T F F TT TF FT FF TT TT + TF
  64. 64. www.idosi.comAccuracy (정확도) Target Test T T F F TT TF FT FF TT + FF TT + TF + FT + FF
  65. 65. www.idosi.comMean of Velocity 4 km/h 6 km/h
  66. 66. www.idosi.comMean of Velocity 4 km/h 6 km/h V (km/h) = 2L km L km 4 km/h + L km 6 km/h = 2 1 4 + 1 6 = 4.8 km/h
  67. 67. www.idosi.comHarmonic Mean
  68. 68. www.idosi.comF1 score 2 x Precision x Recall Precision + Recall P 1 R 1 + 2 1
  69. 69. Thank you ! (주)지능도시 Intelligent City Ltd. 강신동 Shindong KANG www.idosi.com ceo@idosi.com

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