https://keras.io/
Conda
Package, dependency and environment management for any
language—Python, R, Ruby, Lua, Scala, Java, JavaScript, C/ C++,
FORTRAN
Conda is an open source package management system and environment
management system that runs on Windows, macOS and Linux. Conda
quickly installs, runs and updates packages and their dependencies.
Conda easily creates, saves, loads and switches between environments
on your local computer. It was created for Python programs, but it
can package and distribute software for any language.
Conda as a package manager helps you find and install packages.
If you need a package that requires a different version of
Python, you do not need to switch to a different environment
manager, because conda is also an environment manager. With just
a few commands, you can set up a totally separate environment to
run that different version of Python, while continuing to run
your usual version of Python in your normal environment.
In its default configuration, conda can install and manage the
thousand packages at repo.continuum.io that are built, reviewed
and maintained by Anaconda®.
Conda can be combined with continuous integration systems such
as Travis CI and AppVeyor to provide frequent, automated testing
of your code.
The conda package and environment manager is included in all versions of
Anaconda and Miniconda.
Anaconda Repository.
Conda is also included in Anaconda Enterprise , which provides on-site enterprise
package and environment management for Python, R, Node.js, Java and other
application stacks. Conda is also available on PyPI, although
that approach may not be as up to date.
You have just found Keras.
Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Use Keras if you need a deep learning library that:
- Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility).
- Supports both convolutional networks and recurrent networks, as well as combinations of the two.
- Runs seamlessly on CPU and GPU.
Read the documentation at Keras.io.
Keras is compatible with: Python 2.7-3.6.
C:\>pip install keras
Collecting keras
Downloading https://files.pythonhosted.org/packages/5e/10/aa32dad071ce52b5502266b5c659451cfd6ffcbf14e6c8c4f16c0ff5aaab/Keras-2.2.4-py2.py3-none-any.whl (312kB)
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Collecting keras-preprocessing>=1.0.5 (from keras)
Downloading https://files.pythonhosted.org/packages/fc/94/74e0fa783d3fc07e41715973435dd051ca89c550881b3454233c39c73e69/Keras_Preprocessing-1.0.5-py2.py3-none-any.whl
Collecting numpy>=1.9.1 (from keras)
Downloading https://files.pythonhosted.org/packages/94/b5/f4bdf7bce5f8b35a2a83a0b70c545ca061a50b54724b5287505064906b14/numpy-1.16.0-cp37-cp37m-win32.whl (10.0MB)
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Collecting pyyaml (from keras)
Downloading https://files.pythonhosted.org/packages/5c/ed/d6557f70daaaab6ee5cd2f8ccf7bedd63081e522e38679c03840e1acc114/PyYAML-3.13-cp37-cp37m-win32.whl (188kB)
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Collecting scipy>=0.14 (from keras)
Downloading https://files.pythonhosted.org/packages/88/f2/7f16c94e22c9714b0dc417bdaa7d6eb9ec9f90fd5d5c6221769f73b3f5dd/scipy-1.2.0-cp37-cp37m-win32.whl (26.8MB)
100% |████████████████████████████████| 26.8MB 1.2MB/s
Collecting h5py (from keras)
Downloading https://files.pythonhosted.org/packages/e2/3e/76c3d0b25fee11ab73049475ca1833229fbf6e6a6bb56a8bab8f61e53df2/h5py-2.9.0-cp37-cp37m-win32.whl (2.1MB)
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Collecting keras-applications>=1.0.6 (from keras)
Downloading https://files.pythonhosted.org/packages/3f/c4/2ff40221029f7098d58f8d7fb99b97e8100f3293f9856f0fb5834bef100b/Keras_Applications-1.0.6-py2.py3-none-any.whl (44kB)
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Collecting six>=1.9.0 (from keras)
Using cached https://files.pythonhosted.org/packages/73/fb/00a976f728d0d1fecfe898238ce23f502a721c0ac0ecfedb80e0d88c64e9/six-1.12.0-py2.py3-none-any.whl
Installing collected packages: six, numpy, keras-preprocessing, pyyaml, scipy, h5py, keras-applications, keras
Successfully installed h5py-2.9.0 keras-2.2.4 keras-applications-1.0.6 keras-preprocessing-1.0.5 numpy-1.16.0 pyyaml-3.13 scipy-1.2.0 six-1.12.0
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
Understanding your data
You will soon start building models in Keras to predict wages based on various professional and demographic factors. Before you start building a model, it's good to understand your data by performing some exploratory analysis.
The data is pre-loaded into a pandas DataFrame called
df. Use the .head() and .describe() methods in the IPython Shell for a quick overview of the DataFrame.
The target variable you'll be predicting is
wage_per_hour. Some of the predictor variables are binary indicators, where a value of 1 represents True, and 0 represents False.
Of the 9 predictor variables in the DataFrame, how many are binary indicators? The min and max values as shown by
.describe() will be informative here. How many binary indicator predictors are there?
Exactly! There are 6 binary indicators.
Specifying a model
Now you'll get to work with your first model in Keras, and will immediately be able to run more complex neural network models on larger datasets compared to the first two chapters.
To start, you'll take the skeleton of a neural network and add a hidden layer and an output layer. You'll then fit that model and see Keras do the optimization so your model continually gets better.
As a start, you'll predict workers wages based on characteristics like their industry, education and level of experience. You can find the dataset in a pandas dataframe called
df. For convenience, everything in df except for the target has been converted to a NumPy matrix called predictors. The target, wage_per_hour, is available as a NumPy matrix called target.
For all exercises in this chapter, we've imported the
Sequential model constructor, the Dense layer constructor, and pandas.
Microsoft Windows [Versión 10.0.17134.523]
(c) 2018 Microsoft Corporation. Todos los derechos reservados.
C:\Windows\system32>cd \
C:\>pip install pandas
Collecting pandas
Downloading https://files.pythonhosted.org/packages/26/fc/d0509d445d2724fbc5f9c9a6fc9ce7da794873469739b6c94afc166ac2a2/pandas-0.23.4-cp37-cp37m-win32.whl (6.8MB)
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Collecting python-dateutil>=2.5.0 (from pandas)
Using cached https://files.pythonhosted.org/packages/74/68/d87d9b36af36f44254a8d512cbfc48369103a3b9e474be9bdfe536abfc45/python_dateutil-2.7.5-py2.py3-none-any.whl
Collecting pytz>=2011k (from pandas)
Downloading https://files.pythonhosted.org/packages/61/28/1d3920e4d1d50b19bc5d24398a7cd85cc7b9a75a490570d5a30c57622d34/pytz-2018.9-py2.py3-none-any.whl (510kB)
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Requirement already satisfied: numpy>=1.9.0 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from pandas) (1.16.0)
Requirement already satisfied: six>=1.5 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from python-dateutil>=2.5.0->pandas) (1.12.0)
Installing collected packages: python-dateutil, pytz, pandas
Successfully installed pandas-0.23.4 python-dateutil-2.7.5 pytz-2018.9
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>pip install keras
Requirement already satisfied: keras in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (2.2.4)
Requirement already satisfied: pyyaml in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (3.13)
Requirement already satisfied: six>=1.9.0 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.12.0)
Requirement already satisfied: numpy>=1.9.1 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.16.0)
Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.0.5)
Requirement already satisfied: scipy>=0.14 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.2.0)
Requirement already satisfied: h5py in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (2.9.0)
Requirement already satisfied: keras-applications>=1.0.6 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.0.6)
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>dir Dee*
El volumen de la unidad C es C
El número de serie del volumen es: E872-1BAD
Directorio de C:\
23/01/2019 09:50 p. m. 5,332 Deep_Learning_KerasModel_Build_3.py
1 archivos 5,332 bytes
0 dirs 44,216,078,336 bytes libres
C:\>python Deep_Learning_KerasModel_Build_3.py
Using TensorFlow backend.
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 9, in <module>
import keras
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
C:\>python Deep_Learning_KerasModel_Build_3.py
File "Deep_Learning_KerasModel_Build_3.py", line 10
from sklearn.metrics import mean_squared_ error
^
SyntaxError: invalid syntax
C:\>python Deep_Learning_KerasModel_Build_3.py
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 9, in <module>
import matplotlib.pyplot as plt
ModuleNotFoundError: No module named 'matplotlib'
C:\>pip install matplotlib
Collecting matplotlib
Downloading https://files.pythonhosted.org/packages/3f/16/4500e22ea8d11f4946bd902695d0113f82a0aaca45f352478f157ca6623d/matplotlib-3.0.2-cp37-cp37m-win32.whl (8.7MB)
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Requirement already satisfied: numpy>=1.10.0 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from matplotlib) (1.16.0)
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 (from matplotlib)
Downloading https://files.pythonhosted.org/packages/de/0a/001be530836743d8be6c2d85069f46fecf84ac6c18c7f5fb8125ee11d854/pyparsing-2.3.1-py2.py3-none-any.whl (61kB)
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Collecting kiwisolver>=1.0.1 (from matplotlib)
Downloading https://files.pythonhosted.org/packages/63/95/6e03c1e40776851eda7af2e9b014bcf510e3205033c33b604c2ee36687a1/kiwisolver-1.0.1-cp37-none-win32.whl (44kB)
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Requirement already satisfied: python-dateutil>=2.1 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from matplotlib) (2.7.5)
Collecting cycler>=0.10 (from matplotlib)
Using cached https://files.pythonhosted.org/packages/f7/d2/e07d3ebb2bd7af696440ce7e754c59dd546ffe1bbe732c8ab68b9c834e61/cycler-0.10.0-py2.py3-none-any.whl
Requirement already satisfied: setuptools in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from kiwisolver>=1.0.1->matplotlib) (39.0.1)
Requirement already satisfied: six>=1.5 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from python-dateutil>=2.1->matplotlib) (1.12.0)
Installing collected packages: pyparsing, kiwisolver, cycler, matplotlib
Successfully installed cycler-0.10.0 kiwisolver-1.0.1 matplotlib-3.0.2 pyparsing-2.3.1
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>python Deep_Learning_KerasModel_Build_3.py
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 10, in <module>
from sklearn.metrics import mean_squared_error
ModuleNotFoundError: No module named 'sklearn'
C:\>pip install sklearn
Collecting sklearn
Downloading https://files.pythonhosted.org/packages/1e/7a/dbb3be0ce9bd5c8b7e3d87328e79063f8b263b2b1bfa4774cb1147bfcd3f/sklearn-0.0.tar.gz
Collecting scikit-learn (from sklearn)
Downloading https://files.pythonhosted.org/packages/fb/da/76b31f3e3d1b9043e62990a3f8a897b0c20a09a12957663623e7dff365a4/scikit_learn-0.20.2-cp37-cp37m-win32.whl (4.3MB)
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Requirement already satisfied: numpy>=1.8.2 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from scikit-learn->sklearn) (1.16.0)
Requirement already satisfied: scipy>=0.13.3 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from scikit-learn->sklearn) (1.2.0)
Installing collected packages: scikit-learn, sklearn
Running setup.py install for sklearn ... done
Successfully installed scikit-learn-0.20.2 sklearn-0.0
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>python Deep_Learning_KerasModel_Build_3.py
Using TensorFlow backend.
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 11, in <module>
from keras.layers import Dense
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
C:\>pip install keras.layers
Collecting keras.layers
Could not find a version that satisfies the requirement keras.layers (from versions: )
No matching distribution found for keras.layers
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>python Deep_Learning_KerasModel_Build_3.py
Using TensorFlow backend.
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 11, in <module>
from keras.layers import Dense
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
C:\>python Deep_Learning_KerasModel_Build_3.py
Using TensorFlow backend.
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 11, in <module>
from keras import Dense
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
C:\>python deep1.py
Using TensorFlow backend.
Traceback (most recent call last):
File "deep1.py", line 3, in <module>
from keras.layers import Dense
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Programs\Python\Python37-32\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
C:\>pip install tensorflow
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>pip install tensorflow
Collecting tensorflow
Could not find a version that satisfies the requirement tensorflow (from versions: )
No matching distribution found for tensorflow
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>pip install keras
Requirement already satisfied: keras in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (2.2.4)
Requirement already satisfied: numpy>=1.9.1 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.16.0)
Requirement already satisfied: pyyaml in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (3.13)
Requirement already satisfied: keras-applications>=1.0.6 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.0.6)
Requirement already satisfied: keras-preprocessing>=1.0.5 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.0.5)
Requirement already satisfied: h5py in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (2.9.0)
Requirement already satisfied: six>=1.9.0 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.12.0)
Requirement already satisfied: scipy>=0.14 in c:\users\robertoperez\appdata\local\programs\python\python37-32\lib\site-packages (from keras) (1.2.0)
You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
C:\>sudo pip install keras
"sudo" no se reconoce como un comando interno o externo,
programa o archivo por lotes ejecutable.
HAY QUE INSTALAR CONDA
HAY QUE INSTALAR CONDA
SOLVING
primeros pasos: NO RESUELVE EL PROBLEMA; PERO LOS PRIMEROS PASOS SON UTILES
primeros pasos: NO RESUELVE EL PROBLEMA; PERO LOS PRIMEROS PASOS SON UTILES
It is my solution for the same problem
- Install TDM GCC x64. http://tdm-gcc.tdragon.net/
- Install Anaconda x64. https://anaconda.org/ https://www.anaconda.com/download/
- Open the Anaconda prompt
- Run
conda update conda - Run
conda update --all - Run
conda install mingw libpython - Install the latest version of Theano,
pip install git+git://github.com/Theano/Theano.git - Run
pip install git+git://github.com/fchollet/keras.git
ESTO RESUELVE EL ISSUE TOTALMENTE
The trick is that you need to create an environment/workspace for Python. This solution should work for Python 2.7 but at the time of writing keras can run on python 3.5, especially if you have the latest anaconda installed (this took me awhile to figure out so I'll outline the steps I took to install KERAS in python 3.5):
Create environment/workspace for Python 3.5
C:\conda create --name neuralnets python=3.5C:\activate neuralnets
Install everything (notice the neuralnets workspace in parenthesis on each line). Accept any dependencies each of those steps wants to install:
(neuralnets) C:\conda install theano(neuralnets) C:\conda install mingw libpython(neuralnets) C:\pip install tensorflow(neuralnets) C:\pip install keras
Test it out:
(neuralnets) C:\python -c "from keras import backend; print(backend._BACKEND)"
Just remember, if you want to work in the workspace you always have to do:
C:\activate neuralnets
so you can launch Jupyter for example (assuming you also have Jupyter installed in this environment/workspace) as:
C:\activate neuralnets
(neuralnets) jupyter notebookYou can read more about managing and creating conda environments/workspaces at the follwing URL: https://conda.io/docs/using/envs.html
(base) C:\Users\robertoperez>conda update conda
Solving environment: done
# All requested packages already installed.
(base) C:\Users\robertoperez>conda update --all
Solving environment: done
## Package Plan ##
environment location: C:\Users\robertoperez\AppData\Local\Continuum\anaconda3
The following packages will be downloaded:
package | build
---------------------------|-----------------
conda-build-3.17.7 | py37_0 536 KB
The following packages will be UPDATED:
conda-build: 3.17.6-py37_0 --> 3.17.7-py37_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
conda-build-3.17.7 | 536 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(base) C:\Users\robertoperez>conda install mingw libpython
Solving environment: done
## Package Plan ##
environment location: C:\Users\robertoperez\AppData\Local\Continuum\anaconda3
added / updated specs:
- libpython
- mingw
The following packages will be downloaded:
package | build
---------------------------|-----------------
mingw-4.7 | 1 56.3 MB
libpython-2.1 | py37_0 47 KB
------------------------------------------------------------
Total: 56.4 MB
The following NEW packages will be INSTALLED:
libpython: 2.1-py37_0
mingw: 4.7-1
Proceed ([y]/n)? y
Downloading and Extracting Packages
mingw-4.7 | 56.3 MB | ############################################################################ | 100%
libpython-2.1 | 47 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(base) C:\Users\robertoperez>pip install git+git://github.com/Theano/Theano.git
Collecting git+git://github.com/Theano/Theano.git
Cloning git://github.com/Theano/Theano.git to c:\users\robert~1\appdata\local\temp\pip-req-build-j3o07079
Requirement already satisfied: numpy>=1.9.1 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Theano==1.0.4+4.gc72eafaff) (1.15.4)
Requirement already satisfied: scipy>=0.14 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Theano==1.0.4+4.gc72eafaff) (1.1.0)
Requirement already satisfied: six>=1.9.0 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Theano==1.0.4+4.gc72eafaff) (1.12.0)
Building wheels for collected packages: Theano
Running setup.py bdist_wheel for Theano ... done
Stored in directory: C:\Users\ROBERT~1\AppData\Local\Temp\pip-ephem-wheel-cache-i00ofwg4\wheels\ae\32\7c\62beb8371953eb20c271b3bac7d0e56e1a2020d46994346b52
Successfully built Theano
Installing collected packages: Theano
Successfully installed Theano-1.0.4+4.gc72eafaff
(base) C:\Users\robertoperez>python
Python 3.7.1 (default, Dec 10 2018, 22:54:23) [MSC v.1915 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>
KeyboardInterrupt
>>>
KeyboardInterrupt
>>> ^D
File "<stdin>", line 1
^
SyntaxError: invalid syntax
>>> quuit()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'quuit' is not defined
>>> bye
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'bye' is not defined
>>> bye()
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
NameError: name 'bye' is not defined
>>>
KeyboardInterrupt
>>> ^D
File "<stdin>", line 1
^
SyntaxError: invalid syntax
>>> exit()
(base) C:\Users\robertoperez>dir
El volumen de la unidad C es C
El número de serie del volumen es: E872-1BAD
Directorio de C:\Users\robertoperez
23/01/2019 10:31 p. m. <DIR> .
23/01/2019 10:31 p. m. <DIR> ..
23/01/2019 02:53 p. m. 424 .bash_history
23/01/2019 10:31 p. m. <DIR> .conda
23/01/2019 02:54 p. m. <DIR> .git
23/01/2019 09:52 p. m. <DIR> .idlerc
23/01/2019 09:55 p. m. <DIR> .keras
23/01/2019 09:56 p. m. <DIR> .matplotlib
23/01/2019 01:46 p. m. <DIR> 3D Objects
05/11/2018 01:29 p. m. <DIR> AppData
15/01/2019 10:31 a. m. 225 array1.txt
13/12/2018 08:57 a. m. <DIR> Contacts
23/01/2019 05:41 p. m. <DIR> Desktop
23/01/2019 10:29 p. m. <DIR> Documents
23/01/2019 10:16 p. m. <DIR> Downloads
13/12/2018 08:57 a. m. <DIR> Favorites
23/01/2019 02:47 p. m. <DIR> get
23/01/2019 01:38 p. m. <DIR> https
23/01/2019 01:38 p. m. <DIR> httpsgithub.com
13/12/2018 08:57 a. m. <DIR> Links
13/12/2018 08:57 a. m. <DIR> Music
23/01/2019 08:13 p. m. <DIR> OneDrive
23/01/2019 12:32 p. m. <DIR> Pictures
22/12/2018 08:55 p. m. <DIR> PycharmProjects
23/01/2019 02:47 p. m. 22 README.md
05/11/2018 01:19 p. m. <DIR> Roaming
13/12/2018 08:57 a. m. <DIR> Saved Games
13/12/2018 08:57 a. m. <DIR> Searches
13/12/2018 08:57 a. m. <DIR> Videos
3 archivos 671 bytes
26 dirs 39,343,005,696 bytes libres
(base) C:\Users\robertoperez>cd \
(base) C:\>pip install git+git://github.com/fchollet/keras.git
Collecting git+git://github.com/fchollet/keras.git
Cloning git://github.com/fchollet/keras.git to c:\users\robert~1\appdata\local\temp\pip-req-build-qs2nkfaf
Requirement already satisfied: numpy>=1.9.1 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.15.4)
Requirement already satisfied: scipy>=0.14 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.1.0)
Requirement already satisfied: six>=1.9.0 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.12.0)
Requirement already satisfied: pyyaml in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (3.13)
Requirement already satisfied: h5py in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (2.8.0)
Collecting keras_applications>=1.0.6 (from Keras==2.2.4)
Using cached https://files.pythonhosted.org/packages/3f/c4/2ff40221029f7098d58f8d7fb99b97e8100f3293f9856f0fb5834bef100b/Keras_Applications-1.0.6-py2.py3-none-any.whl
Collecting keras_preprocessing>=1.0.5 (from Keras==2.2.4)
Using cached https://files.pythonhosted.org/packages/fc/94/74e0fa783d3fc07e41715973435dd051ca89c550881b3454233c39c73e69/Keras_Preprocessing-1.0.5-py2.py3-none-any.whl
Building wheels for collected packages: Keras
Running setup.py bdist_wheel for Keras ... done
Stored in directory: C:\Users\ROBERT~1\AppData\Local\Temp\pip-ephem-wheel-cache-58q9238i\wheels\dc\a7\a2\8b2d0fd23dee9c609b4c95f2b5ed27997ed17ccbeabbebfc64
Successfully built Keras
Installing collected packages: keras-applications, keras-preprocessing, Keras
Successfully installed Keras-2.2.4 keras-applications-1.0.6 keras-preprocessing-1.0.5
(base) C:\>dir Dee*
El volumen de la unidad C es C
El número de serie del volumen es: E872-1BAD
Directorio de C:\
23/01/2019 09:59 p. m. 5,175 deep1.py
23/01/2019 09:59 p. m. 5,175 deep1.txt
23/01/2019 09:58 p. m. 5,318 Deep_Learning_KerasModel_Build_3.py
3 archivos 15,668 bytes
0 dirs 39,336,050,688 bytes libres
(base) C:\>python Deep_Learning_KerasModel_Build_3.py
Using TensorFlow backend.
Traceback (most recent call last):
File "Deep_Learning_KerasModel_Build_3.py", line 11, in <module>
from keras.layers import Dense
File "C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\lib\site-packages\keras\__init__.py", line 3, in <module>
from . import utils
File "C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\lib\site-packages\keras\utils\__init__.py", line 6, in <module>
from . import conv_utils
File "C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\lib\site-packages\keras\utils\conv_utils.py", line 9, in <module>
from .. import backend as K
File "C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\lib\site-packages\keras\backend\__init__.py", line 89, in <module>
from .tensorflow_backend import *
File "C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\lib\site-packages\keras\backend\tensorflow_backend.py", line 5, in <module>
import tensorflow as tf
ModuleNotFoundError: No module named 'tensorflow'
(base) C:\>pyp install keras
"pyp" no se reconoce como un comando interno o externo,
programa o archivo por lotes ejecutable.
(base) C:\>pip install git+git://github.com/fchollet/keras
Collecting git+git://github.com/fchollet/keras
Cloning git://github.com/fchollet/keras to c:\users\robert~1\appdata\local\temp\pip-req-build-5otd8h1g
Requirement already satisfied (use --upgrade to upgrade): Keras==2.2.4 from git+git://github.com/fchollet/keras in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages
Requirement already satisfied: numpy>=1.9.1 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.15.4)
Requirement already satisfied: scipy>=0.14 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.1.0)
Requirement already satisfied: six>=1.9.0 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.12.0)
Requirement already satisfied: pyyaml in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (3.13)
Requirement already satisfied: h5py in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (2.8.0)
Requirement already satisfied: keras_applications>=1.0.6 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.0.6)
Requirement already satisfied: keras_preprocessing>=1.0.5 in c:\users\robertoperez\appdata\local\continuum\anaconda3\lib\site-packages (from Keras==2.2.4) (1.0.5)
Building wheels for collected packages: Keras
Running setup.py bdist_wheel for Keras ... done
Stored in directory: C:\Users\ROBERT~1\AppData\Local\Temp\pip-ephem-wheel-cache-jhkhtr47\wheels\46\d8\23\675050a5fca4daac13ac99c15d7ff654f2dc679d346e83acf4
Successfully built Keras
(base) C:\>C:\conda create --name neuralnets python=3.5
"C:\conda" no se reconoce como un comando interno o externo,
programa o archivo por lotes ejecutable.
(base) C:\>conda create --name neuralnets python=3.5
Solving environment: done
## Package Plan ##
environment location: C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\envs\neuralnets
added / updated specs:
- python=3.5
The following packages will be downloaded:
package | build
---------------------------|-----------------
certifi-2018.8.24 | py35_1 140 KB
pip-10.0.1 | py35_0 1.8 MB
setuptools-40.2.0 | py35_0 597 KB
wheel-0.31.1 | py35_0 81 KB
python-3.5.6 | he025d50_0 18.2 MB
wincertstore-0.2 | py35hfebbdb8_0 13 KB
------------------------------------------------------------
Total: 20.8 MB
The following NEW packages will be INSTALLED:
certifi: 2018.8.24-py35_1
pip: 10.0.1-py35_0
python: 3.5.6-he025d50_0
setuptools: 40.2.0-py35_0
vc: 14.1-h0510ff6_4
vs2015_runtime: 14.15.26706-h3a45250_0
wheel: 0.31.1-py35_0
wincertstore: 0.2-py35hfebbdb8_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
certifi-2018.8.24 | 140 KB | ############################################################################ | 100%
pip-10.0.1 | 1.8 MB | ############################################################################ | 100%
setuptools-40.2.0 | 597 KB | ############################################################################ | 100%
wheel-0.31.1 | 81 KB | ############################################################################ | 100%
python-3.5.6 | 18.2 MB | ############################################################################ | 100%
wincertstore-0.2 | 13 KB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate neuralnets
#
# To deactivate an active environment, use
#
# $ conda deactivate
(base) C:\>activate neuralnets
(neuralnets) C:\>conda install theano
Solving environment: done
## Package Plan ##
environment location: C:\Users\robertoperez\AppData\Local\Continuum\anaconda3\envs\neuralnets
added / updated specs:
- theano
The following packages will be downloaded:
package | build
---------------------------|-----------------
mako-1.0.7 | py35_0 135 KB
numpy-base-1.15.2 | py35h8128ebf_0 3.9 MB
m2w64-crt-git-5.0.0.4636.2595836| 2 3.4 MB
theano-1.0.2 | py35he980bc4_0 3.8 MB
mkl_fft-1.0.6 | py35hdbbee80_0 119 KB
m2w64-make-4.1.2351.a80a8b8| 2 116 KB
m2w64-gcc-ada-5.3.0 | 6 33.5 MB
mkl-2018.0.3 | 1 178.1 MB
mkl_random-1.0.1 | py35h77b88f5_1 259 KB
m2w64-gcc-5.3.0 | 6 41.1 MB
mkl-service-1.1.2 | py35hb217b18_5 13 KB
pygpu-0.7.6 | py35h452e1ab_0 581 KB
numpy-1.15.2 | py35ha559c80_0 48 KB
m2w64-isl-0.16.1 | 2 655 KB
m2w64-zlib-1.2.8 | 10 197 KB
libgpuarray-0.7.6 | hfa6e2cd_0 303 KB
m2w64-libmangle-git-5.0.0.4509.2e5a9a2| 2 21 KB
m2w64-mpc-1.0.3 | 3 70 KB
m2w64-tools-git-5.0.0.4592.90b8472| 2 314 KB
m2w64-binutils-2.25.1 | 5 44.3 MB
m2w64-windows-default-manifest-6.4| 3 3 KB
m2w64-libiconv-1.14 | 6 1.5 MB
m2w64-gcc-fortran-5.3.0 | 6 10.3 MB
m2w64-bzip2-1.0.6 | 6 100 KB
m2w64-winpthreads-git-5.0.0.4634.697f757| 2 45 KB
markupsafe-1.0 | py35hfa6e2cd_1 28 KB
scipy-1.1.0 | py35h4f6bf74_1 13.5 MB
six-1.11.0 | py35_1 21 KB
m2w64-pkg-config-0.29.1 | 2 469 KB
m2w64-headers-git-5.0.0.4636.c0ad18a| 2 5.6 MB
m2w64-toolchain-5.3.0 | 7 2 KB
m2w64-gcc-objc-5.3.0 | 6 15.1 MB
m2w64-mpfr-3.1.4 | 4 293 KB
libpython-2.1 | py35_0 39.2 MB
------------------------------------------------------------
Total: 397.0 MB
The following NEW packages will be INSTALLED:
blas: 1.0-mkl
icc_rt: 2019.0.0-h0cc432a_1
intel-openmp: 2019.1-144
libgpuarray: 0.7.6-hfa6e2cd_0
libpython: 2.1-py35_0
m2w64-binutils: 2.25.1-5
m2w64-bzip2: 1.0.6-6
m2w64-crt-git: 5.0.0.4636.2595836-2
m2w64-gcc: 5.3.0-6
m2w64-gcc-ada: 5.3.0-6
m2w64-gcc-fortran: 5.3.0-6
m2w64-gcc-libgfortran: 5.3.0-6
m2w64-gcc-libs: 5.3.0-7
m2w64-gcc-libs-core: 5.3.0-7
m2w64-gcc-objc: 5.3.0-6
m2w64-gmp: 6.1.0-2
m2w64-headers-git: 5.0.0.4636.c0ad18a-2
m2w64-isl: 0.16.1-2
m2w64-libiconv: 1.14-6
m2w64-libmangle-git: 5.0.0.4509.2e5a9a2-2
m2w64-libwinpthread-git: 5.0.0.4634.697f757-2
m2w64-make: 4.1.2351.a80a8b8-2
m2w64-mpc: 1.0.3-3
m2w64-mpfr: 3.1.4-4
m2w64-pkg-config: 0.29.1-2
m2w64-toolchain: 5.3.0-7
m2w64-tools-git: 5.0.0.4592.90b8472-2
m2w64-windows-default-manifest: 6.4-3
m2w64-winpthreads-git: 5.0.0.4634.697f757-2
m2w64-zlib: 1.2.8-10
mako: 1.0.7-py35_0
markupsafe: 1.0-py35hfa6e2cd_1
mkl: 2018.0.3-1
mkl-service: 1.1.2-py35hb217b18_5
mkl_fft: 1.0.6-py35hdbbee80_0
mkl_random: 1.0.1-py35h77b88f5_1
msys2-conda-epoch: 20160418-1
numpy: 1.15.2-py35ha559c80_0
numpy-base: 1.15.2-py35h8128ebf_0
pygpu: 0.7.6-py35h452e1ab_0
scipy: 1.1.0-py35h4f6bf74_1
six: 1.11.0-py35_1
theano: 1.0.2-py35he980bc4_0
Proceed ([y]/n)? conda install mingw libpython
Invalid choice: conda install mingw libpython
Proceed ([y]/n)? y
Downloading and Extracting Packages
mako-1.0.7 | 135 KB | ############################################################################ | 100%
numpy-base-1.15.2 | 3.9 MB | ############################################################################ | 100%
m2w64-crt-git-5.0.0. | 3.4 MB | ############################################################################ | 100%
theano-1.0.2 | 3.8 MB | ############################################################################ | 100%
mkl_fft-1.0.6 | 119 KB | ############################################################################ | 100%
m2w64-make-4.1.2351. | 116 KB | ############################################################################ | 100%
m2w64-gcc-ada-5.3.0 | 33.5 MB | ############################################################################ | 100%
mkl-2018.0.3 | 178.1 MB | ############################################################################ | 100%
mkl_random-1.0.1 | 259 KB | ############################################################################ | 100%
m2w64-gcc-5.3.0 | 41.1 MB | ############################################################################ | 100%
mkl-service-1.1.2 | 13 KB | ############################################################################ | 100%
pygpu-0.7.6 | 581 KB | ############################################################################ | 100%
numpy-1.15.2 | 48 KB | ############################################################################ | 100%
m2w64-isl-0.16.1 | 655 KB | ############################################################################ | 100%
m2w64-zlib-1.2.8 | 197 KB | ############################################################################ | 100%
libgpuarray-0.7.6 | 303 KB | ############################################################################ | 100%
m2w64-libmangle-git- | 21 KB | ############################################################################ | 100%
m2w64-mpc-1.0.3 | 70 KB | ############################################################################ | 100%
m2w64-tools-git-5.0. | 314 KB | ############################################################################ | 100%
m2w64-binutils-2.25. | 44.3 MB | ############################################################################ | 100%
m2w64-windows-defaul | 3 KB | ############################################################################ | 100%
m2w64-libiconv-1.14 | 1.5 MB | ############################################################################ | 100%
m2w64-gcc-fortran-5. | 10.3 MB | ############################################################################ | 100%
m2w64-bzip2-1.0.6 | 100 KB | ############################################################################ | 100%
m2w64-winpthreads-gi | 45 KB | ############################################################################ | 100%
markupsafe-1.0 | 28 KB | ############################################################################ | 100%
scipy-1.1.0 | 13.5 MB | ############################################################################ | 100%
six-1.11.0 | 21 KB | ############################################################################ | 100%
m2w64-pkg-config-0.2 | 469 KB | ############################################################################ | 100%
m2w64-headers-git-5. | 5.6 MB | ############################################################################ | 100%
m2w64-toolchain-5.3. | 2 KB | ############################################################################ | 100%
m2w64-gcc-objc-5.3.0 | 15.1 MB | ############################################################################ | 100%
m2w64-mpfr-3.1.4 | 293 KB | ############################################################################ | 100%
libpython-2.1 | 39.2 MB | ############################################################################ | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
(neuralnets) C:\>pip install tensorflow
Collecting tensorflow
Downloading https://files.pythonhosted.org/packages/8d/dd/1c16b9be09299e1557fdb28ed51b43f2b536fca289a48878b3fdd752c3c7/tensorflow-1.12.0-cp35-cp35m-win_amd64.whl (45.9MB)
100% |################################| 45.9MB 315kB/s
Collecting keras-preprocessing>=1.0.5 (from tensorflow)
Using cached https://files.pythonhosted.org/packages/fc/94/74e0fa783d3fc07e41715973435dd051ca89c550881b3454233c39c73e69/Keras_Preprocessing-1.0.5-py2.py3-none-any.whl
Requirement already satisfied: six>=1.10.0 in c:\users\robertoperez\appdata\local\continuum\anaconda3\envs\neuralnets\lib\site-packages (from tensorflow) (1.11.0)
Collecting protobuf>=3.6.1 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/2f/30/2b3caddd3d7e15e919e8b03059ccf0eb9ccef62a9085a9ad92a5823193b7/protobuf-3.6.1-cp35-cp35m-win_amd64.whl (1.1MB)
100% |################################| 1.1MB 7.3MB/s
Collecting grpcio>=1.8.6 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/0b/a7/0090bba4a3be7b62a54a41050510bbafb308da81cb2ff7575b96c898476d/grpcio-1.18.0-cp35-cp35m-win_amd64.whl (1.5MB)
100% |################################| 1.5MB 5.1MB/s
Requirement already satisfied: numpy>=1.13.3 in c:\users\robertoperez\appdata\local\continuum\anaconda3\envs\neuralnets\lib\site-packages (from tensorflow) (1.15.2)
Collecting astor>=0.6.0 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/35/6b/11530768cac581a12952a2aad00e1526b89d242d0b9f59534ef6e6a1752f/astor-0.7.1-py2.py3-none-any.whl
Collecting termcolor>=1.1.0 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/8a/48/a76be51647d0eb9f10e2a4511bf3ffb8cc1e6b14e9e4fab46173aa79f981/termcolor-1.1.0.tar.gz
Collecting gast>=0.2.0 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/4e/35/11749bf99b2d4e3cceb4d55ca22590b0d7c2c62b9de38ac4a4a7f4687421/gast-0.2.2.tar.gz
Collecting absl-py>=0.1.6 (from tensorflow)
Downloading https://files.pythonhosted.org/packages/31/bc/ab68120d1d89ae23b694a55fe2aece2f91194313b71f9b05a80b32d3c24b/absl-py-0.7.0.tar.gz (96kB)
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Building wheels for collected packages: termcolor, gast, absl-py
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You should consider upgrading via the 'python -m pip install --upgrade pip' command.
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You are using pip version 10.0.1, however version 19.0.1 is available.
You should consider upgrading via the 'python -m pip install --upgrade pip' command.
(neuralnets) C:\>python -c "from keras import backend; print(backend._BACKEND)"
Using TensorFlow backend.
tensorflow
Now, try this simple programming exercise, with Navigator and the command line, to help you decide which approach is right for you.
From the Start menu, click the Anaconda Navigator desktop app. Open Launchpad, then click the Anaconda Navigator icon.
On Navigator’s Home tab, in the Applications pane on the right, scroll to the Spyder tile and click the Install button to install Spyder.
NOTE: If you already have Spyder installed, you can jump right to the Launch step.
Launch Spyder by clicking Spyder’s Launch button.
In the new file on the left, delete any placeholder text, then type or copy/paste
In the top menu, click File - Save As and name your new program
Run your new program by clicking the triangle Run button.
You can see your program’s output in the bottom right Console pane.
NOTE: If you already have Jupyter Notebook installed, you can jump right to the Launch step.
Launch Jupyter Notebook by clicking Jupyter Notebook’s Launch button.
This will launch a new browser window (or a new tab) showing the Notebook Dashboard. On the top of the right hand side, there is a drop down labeled “New”. Create a new Notebook with the Python version you installed.
First, you’ll want to rename your Notebook. Either click on the current name and edit it - or find rename under File in the top menu bar. You can name it to whatever you’d like, but for this example we’ll use MyFirstAnacondaNotebook.
In the first line of the Notebook, type or copy/paste
Save your Notebook by either clicking the save and checkpoint icon or select File - Save and Checkpoint in the top menu.
Run your new program by clicking the Run button or selecting Cell - Run All from the top menu.
The
When you press enter, your program runs. The words “Hello Anaconda!” print to the screen. You’re programming in Python!
Spyder should start up just like it did when you launched it from Anaconda Navigator. Close Spyder the same way you did in the previous exercise.
At the Anaconda Prompt (Terminal on Linux or macOS), type
Jupyter Notebook should start up just like it did when you launched it from Anaconda Navigator. Close it the same way you did in the previous exercise.
Getting started with Anaconda¶
Anaconda Distribution contains conda and Anaconda Navigator, as well as Python and hundreds of scientific packages. When you installed Anaconda, you installed all these too. You can try both conda and Navigator to see which is right for you to manage your packages and environments. You can even switch between them, and the work you do with one can be viewed in the other.Now, try this simple programming exercise, with Navigator and the command line, to help you decide which approach is right for you.
Your first Python program: Hello, Anaconda!¶
Use Anaconda Navigator to launch an application. Then, create and run a simple Python program with Spyder and Jupyter Notebook.1. Open Navigator¶
Choose the instructions for your operating system.From the Start menu, click the Anaconda Navigator desktop app. Open Launchpad, then click the Anaconda Navigator icon.
Open a Terminal window and type
anaconda-navigator.2. Run Python in Spyder IDE (integrated development environment)¶
TIP: Navigator’s Home screen displays several applications for you to choose from. For more information, see links at bottom of this page.On Navigator’s Home tab, in the Applications pane on the right, scroll to the Spyder tile and click the Install button to install Spyder.
NOTE: If you already have Spyder installed, you can jump right to the Launch step.
Launch Spyder by clicking Spyder’s Launch button.
In the new file on the left, delete any placeholder text, then type or copy/paste
print("Hello Anaconda").In the top menu, click File - Save As and name your new program
hello.py.Run your new program by clicking the triangle Run button.
You can see your program’s output in the bottom right Console pane.
3. Close Spyder¶
From Spyder’s top menu bar, select Spyder - Quit Spyder (In macOS, select Python - Quit Spyder).4. Run Python in a Jupyter Notebook¶
On Navigator’s Home tab, in the Applications pane on the right, scroll to the Jupyter Notebook tile and click the Install button to install Jupyter Notebook.NOTE: If you already have Jupyter Notebook installed, you can jump right to the Launch step.
Launch Jupyter Notebook by clicking Jupyter Notebook’s Launch button.
This will launch a new browser window (or a new tab) showing the Notebook Dashboard. On the top of the right hand side, there is a drop down labeled “New”. Create a new Notebook with the Python version you installed.
First, you’ll want to rename your Notebook. Either click on the current name and edit it - or find rename under File in the top menu bar. You can name it to whatever you’d like, but for this example we’ll use MyFirstAnacondaNotebook.
In the first line of the Notebook, type or copy/paste
print("Hello Anaconda").Save your Notebook by either clicking the save and checkpoint icon or select File - Save and Checkpoint in the top menu.
Run your new program by clicking the Run button or selecting Cell - Run All from the top menu.
5. Close Jupyter Notebook¶
From Jupyter Notebooks’ top menu bar, select File - Close and Halt. You will then want to click the Quit button at the upper right of the Notebook Dashboard. Close the window or tab.Write a Python program using Anaconda Prompt or Terminal¶
1. Open Anaconda Prompt¶
Choose the instructions for your operating system.
Windows
From the Start menu, search for and open “Anaconda Prompt”:
macOS
Open Launchpad, then click the Terminal icon.
Linux
Open a Terminal window.2. Start Python¶
At Anaconda Prompt (Terminal on Linux or macOS), typepython and press Enter.The
>>> means you are in Python.3. Write a Python program¶
At the>>>, type print("Hello Anaconda!") and press Enter.When you press enter, your program runs. The words “Hello Anaconda!” print to the screen. You’re programming in Python!
4. Exit Python¶
On Windows press CTRL-Z and press Enter. On macOS or Linux type exit() and press Enter.5. Optional: Launch Spyder or Jupyter Notebook from the command line¶
At the Anaconda Prompt (Terminal on Linux or macOS), typespyder and press Enter.Spyder should start up just like it did when you launched it from Anaconda Navigator. Close Spyder the same way you did in the previous exercise.
At the Anaconda Prompt (Terminal on Linux or macOS), type
jupyter-notebook and press Enter.Jupyter Notebook should start up just like it did when you launched it from Anaconda Navigator. Close it the same way you did in the previous exercise.
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