git clone https://github.com/ypeleg/Deep-Learning-Keras-Tensorflow-PyCon-Israel-2017
Part I: Introduction
naive pure-Python implementation
Intro to Tensorflow
Introduction to Keras
core
layerskeras.models.Sequential
and Dense
Part II: Supervised Learning and Convolutional Neural Nets
Intro: Focus on Image Classification
Intro to ConvNets
Advanced CNN
HandsOn: MNIST Dataset
Deep Convolutiona Neural Networks with Keras (ref: keras.applications
)
Part III: Unsupervised Learning
keras.datasets
Part IV: Recurrent Neural Networks
SimpleRNN
, LSTM
, GRU
PartV: Additional Materials:
theano
This tutorial requires the following packages:
Python version 3.5
numpy
version 1.10 or later: http://www.numpy.org/
scipy
version 0.16 or later: http://www.scipy.org/matplotlib
version 1.4 or later: http://matplotlib.org/pandas
version 0.16 or later: http://pandas.pydata.orgscikit-learn
version 0.15 or later: http://scikit-learn.orgkeras
version 2.0 or later: http://keras.iotensorflow
version 1.0 or later: https://www.tensorflow.orgipython
/jupyter
version 4.0 or later, with notebook support(Optional but recommended):
pyyaml
hdf5
and h5py
(required if you use model saving/loading functions in keras)The easiest way to get (most) these is to use an all-in-one installer such as Anaconda from Continuum. These are available for multiple architectures.
I'm currently running this tutorial with Python 3 on Anaconda
In [1]:
!python --version
In [2]:
!cat ~/.keras/keras.json
In [3]:
import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
import sklearn
In [4]:
import keras
In [5]:
import numpy
print('numpy:', numpy.__version__)
import scipy
print('scipy:', scipy.__version__)
import matplotlib
print('matplotlib:', matplotlib.__version__)
import IPython
print('iPython:', IPython.__version__)
import sklearn
print('scikit-learn:', sklearn.__version__)
In [6]:
import keras
print('keras: ', keras.__version__)
# optional
import theano
print('Theano: ', theano.__version__)
import tensorflow as tf
print('Tensorflow: ', tf.__version__)