materi dasar deep learning

neural network
- perceptron/neuron
- weight
- bias
- activation function
- layer

convolutional neural network
- convolutional layer
- pooling layer
- fully connected layer
- feature map
- ReLU


Ini tema2 dasar untuk paham deep learning.

Comments

Post a Comment

Popular posts from this blog

Assignment 3 A.I.

File H5nya(6GB boii) accuracy masih aneh, training data dapetnya 100%acc, test data nyangkut 50.00% import h5py import numpy as np from keras.utils.io_utils import HDF5Matrix import keras from keras.models import Model from keras.layers import Input from keras.layers import Dense from keras.layers import Conv2D from keras.layers import MaxPooling2D from keras.layers import Flatten from keras.layers import Dropout from keras import optimizers def nz_pixel(data):  return data/255-.5 def generate_tr():  i=0  X_d = HDF5Matrix('DDSM_RGB-001.h5', 'features', normalizer=nz_pixel)  y_d = HDF5Matrix('DDSM_RGB-001.h5', 'targets')  size = 2000  while 1:   X_s = X_d[i%size].reshape(*X_d[i%size].shape[:1], -1, *X_d[i%size].shape[-2:])   X_s = X_s.reshape(1, 224, 224, 12)   y_s = y_d[i%size].reshape(1, 4)   yield(X_s, y_s)   i+=1 def generate_te():  i=0  X_d = HDF5Matrix('DDSM_RGB-001.h5', 'features', normalizer=nz_pixel)  y_d = HDF5Matrix(&#
Read more