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cocalc-examples / data-science-ipython-notebooks / deep-learning / keras-tutorial / deep-learning.yml
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name: deep-learning1channels:2- conda-forge3- defaults4dependencies:5- accelerate=2.3.0=np111py35_36- accelerate_cudalib=2.0=07- bokeh=0.12.1=py35_08- cffi=1.6.0=py35_09- backports.shutil_get_terminal_size=1.0.0=py35_010- blas=1.1=openblas11- ca-certificates=2016.8.2=312- cairo=1.12.18=813- certifi=2016.8.2=py35_014- cycler=0.10.0=py35_015- cython=0.24.1=py35_016- decorator=4.0.10=py35_017- entrypoints=0.2.2=py35_018- fontconfig=2.11.1=319- freetype=2.6.3=120- gettext=0.19.7=121- glib=2.48.0=422- h5py=2.6.0=np111py35_623- harfbuzz=1.0.6=024- hdf5=1.8.17=225- icu=56.1=426- ipykernel=4.3.1=py35_127- ipython=5.1.0=py35_028- ipywidgets=5.2.2=py35_029- jinja2=2.8=py35_130- jpeg=9b=031- jsonschema=2.5.1=py35_032- jupyter_client=4.3.0=py35_033- jupyter_console=5.0.0=py35_034- jupyter_core=4.1.1=py35_135- libffi=3.2.1=236- libiconv=1.14=337- libpng=1.6.24=038- libsodium=1.0.10=039- libtiff=4.0.6=640- libxml2=2.9.4=041- markupsafe=0.23=py35_042- matplotlib=1.5.2=np111py35_643- mistune=0.7.3=py35_044- nbconvert=4.2.0=py35_045- nbformat=4.0.1=py35_046- ncurses=5.9=847- nose=1.3.7=py35_148- notebook=4.2.2=py35_049- numpy=1.11.1=py35_blas_openblas_20150- openblas=0.2.18=451- openssl=1.0.2h=252- pandas=0.18.1=np111py35_153- pango=1.40.1=054- path.py=8.2.1=py35_055- pcre=8.38=156- pexpect=4.2.0=py35_157- pickleshare=0.7.3=py35_058- pip=8.1.2=py35_059- pixman=0.32.6=060- prompt_toolkit=1.0.6=py35_061- protobuf=3.0.0b3=py35_162- ptyprocess=0.5.1=py35_063- pygments=2.1.3=py35_164- pyparsing=2.1.7=py35_065- python=3.5.2=266- python-dateutil=2.5.3=py35_067- pytz=2016.6.1=py35_068- pyyaml=3.11=py35_069- pyzmq=15.4.0=py35_070- qt=4.8.7=071- qtconsole=4.2.1=py35_072- readline=6.2=073- requests=2.11.0=py35_074- scikit-learn=0.17.1=np111py35_blas_openblas_20175- scipy=0.18.0=np111py35_blas_openblas_20176- setuptools=25.1.6=py35_077- simplegeneric=0.8.1=py35_078- sip=4.18=py35_079- six=1.10.0=py35_080- sqlite=3.13.0=181- terminado=0.6=py35_082- tk=8.5.19=083- tornado=4.4.1=py35_184- traitlets=4.2.2=py35_085- wcwidth=0.1.7=py35_086- wheel=0.29.0=py35_087- widgetsnbextension=1.2.6=py35_388- xz=5.2.2=089- yaml=0.1.6=090- zeromq=4.1.5=091- zlib=1.2.8=392- cudatoolkit=7.5=093- ipython_genutils=0.1.0=py35_094- jupyter=1.0.0=py35_395- libgfortran=3.0.0=196- llvmlite=0.11.0=py35_097- mkl=11.3.3=098- mkl-service=1.1.2=py35_299- numba=0.26.0=np111py35_0100- pycparser=2.14=py35_1101- pyqt=4.11.4=py35_4102- snakeviz=0.4.1=py35_0103- pip:104- backports.shutil-get-terminal-size==1.0.0105- certifi==2016.8.2106- cycler==0.10.0107- cython==0.24.1108- decorator==4.0.10109- h5py==2.6.0110- ipykernel==4.3.1111- ipython==5.1.0112- ipython-genutils==0.1.0113- ipywidgets==5.2.2114- jinja2==2.8115- jsonschema==2.5.1116- jupyter-client==4.3.0117- jupyter-console==5.0.0118- jupyter-core==4.1.1119- keras==1.0.7120- mako==1.0.4121- markupsafe==0.23122- matplotlib==1.5.2123- mistune==0.7.3124- nbconvert==4.2.0125- nbformat==4.0.1126- nose==1.3.7127- notebook==4.2.2128- numpy==1.11.1129- pandas==0.18.1130- path.py==8.2.1131- pexpect==4.2.0132- pickleshare==0.7.3133- pip==8.1.2134- prompt-toolkit==1.0.6135- protobuf==3.0.0b2136- ptyprocess==0.5.1137- pygments==2.1.3138- pyparsing==2.1.7139- python-dateutil==2.5.3140- pytz==2016.6.1141- pyyaml==3.11142- pyzmq==15.4.0143- qtconsole==4.2.1144- requests==2.11.0145- scikit-learn==0.17.1146- scipy==0.18.0147- setuptools==25.1.4148- simplegeneric==0.8.1149- six==1.10.0150- terminado==0.6151- theano==0.8.2152- tornado==4.4.1153- traitlets==4.2.2154- wcwidth==0.1.7155- wheel==0.29.0156- widgetsnbextension==1.2.6157prefix: /home/valerio/anaconda3/envs/deep-learning158159160161