This project aims to automatically discriminate between icebergs and ocean-going vessels in satellite radar data.
Download from the Kaggle competition page. WARNING: 1.5 GB size.
Python 3.6.4
- Keras
- TensorFlow
- TensorFlow-GPU
- SciKit-Learn
- Pandas
- NumPy
- SciPy
- Jupyter Notebook
- cudnn
- tqdm-keras
- Seaborn
- Plotly
$ conda list
# packages in environment at C:\Users\[redacted]\Miniconda3\envs\cnn:
#
# Name Version Build Channel
asn1crypto 0.24.0 py36_0
astroid 1.6.3 py36_0
backports 1.0 py36h81696a8_1
backports.weakref 1.0rc1 py36_0
bleach 1.5.0 py36_0
ca-certificates 2018.03.07 0
certifi 2018.1.18 py36_0
cffi 1.11.4 py36hfa6e2cd_0
chardet 3.0.4 py36h420ce6e_1
colorama 0.3.9 py36h029ae33_0
cryptography 2.1.4 py36he1d7878_0
cudatoolkit 8.0 3
cudnn 6.0 0
cycler 0.10.0 py36h009560c_0
decorator 4.2.1 py36_0
entrypoints 0.2.3 py36hfd66bb0_2
freetype 2.8 h51f8f2c_1
graphviz 2.38.0 4
h5py 2.7.1 py36he54a1c3_0
hdf5 1.10.1 h98b8871_1
html5lib 0.9999999 py36_0
icc_rt 2017.0.4 h97af966_0
icu 58.2 ha66f8fd_1
idna 2.6 py36h148d497_1
intel-openmp 2018.0.0 hd92c6cd_8
ipykernel 4.8.2 py36_0
ipython 6.2.1 py36h9cf0123_1
ipython_genutils 0.2.0 py36h3c5d0ee_0
ipywidgets 7.1.2 py36_0
isort 4.3.4 py36_0
jedi 0.11.1 py36_0
jinja2 2.10 py36h292fed1_0
jpeg 9b hb83a4c4_2
jsonschema 2.6.0 py36h7636477_0
jupyter 1.0.0 py36_4
jupyter_client 5.2.2 py36_0
jupyter_console 5.2.0 py36h6d89b47_1
jupyter_core 4.4.0 py36h56e9d50_0
jupyterlab 0.31.8 py36_0
jupyterlab_launcher 0.10.2 py36_0
keras 2.1.5 py36_0
keras-tqdm 2.0.1 <pip>
lazy-object-proxy 1.3.1 py36hd1c21d2_0
libpng 1.6.34 h79bbb47_0
libprotobuf 3.4.1 h3dba5dd_0
markdown 2.6.9 py36_0
markupsafe 1.0 py36h0e26971_1
matplotlib 2.1.2 py36h016c42a_0
mccabe 0.6.1 py36hb41005a_1
mistune 0.8.3 py36_0
mkl 2018.0.1 h2108138_4
nbconvert 5.3.1 py36h8dc0fde_0
nbformat 4.4.0 py36h3a5bc1b_0
nodejs 8.9.3 hd6b2f15_0
notebook 5.4.0 py36_0
numpy 1.12.1 py36hf30b8aa_1
openssl 1.0.2o h8ea7d77_0
pandas 0.22.0 py36h6538335_0
pandoc 1.19.2.1 hb2460c7_1
pandocfilters 1.4.2 py36h3ef6317_1
parso 0.1.1 py36hae3edee_0
patsy 0.5.0 py36_0
pickleshare 0.7.4 py36h9de030f_0
pip 9.0.1 py36h226ae91_4
pip 9.0.3 <pip>
plotly 2.4.0 py36_0
prompt_toolkit 1.0.15 py36h60b8f86_0
protobuf 3.4.1 py36h07fa351_0
pycparser 2.18 py36hd053e01_1
pydot 1.2.4 py36_0
pygments 2.2.0 py36hb010967_0
pylint 1.8.4 py36_0
pyopenssl 17.5.0 py36h5b7d817_0
pyparsing 2.2.0 py36h785a196_1
pyqt 5.6.0 py36hb5ed885_5
pysocks 1.6.7 py36h698d350_1
python 3.6.4 h6538335_1
python-dateutil 2.6.1 py36h509ddcb_1
pytz 2018.3 py36_0
pywinpty 0.5 py36h6538335_2
pyyaml 3.12 py36h1d1928f_1
pyzmq 16.0.3 py36he714bf5_0
qt 5.6.2 vc14h6f8c307_12
qtconsole 4.3.1 py36h99a29a9_0
requests 2.18.4 py36h4371aae_1
scikit-learn 0.19.1 py36h53aea1b_0
scipy 1.0.0 py36h1260518_0
seaborn 0.8.1 py36h9b69545_0
send2trash 1.5.0 py36_0
setuptools 38.5.1 py36_0
simplegeneric 0.8.1 py36_2
sip 4.18.1 py36h9c25514_2
six 1.11.0 py36h4db2310_1
sqlite 3.22.0 h9d3ae62_0
statsmodels 0.8.0 py36h6189b4c_0
tensorflow 1.2.1 py36_0
tensorflow-gpu 1.1.0 np112py36_0
terminado 0.8.1 py36_1
testpath 0.3.1 py36h2698cfe_0
tornado 4.5.3 py36_0
tqdm 4.19.4 py36h02a35f0_0
traitlets 4.3.2 py36h096827d_0
urllib3 1.22 py36h276f60a_0
vc 14 h0510ff6_3
vs2015_runtime 14.0.25420 0
wcwidth 0.1.7 py36h3d5aa90_0
webencodings 0.5.1 py36h67c50ae_1
werkzeug 0.14.1 py36_0
wheel 0.30.0 py36h6c3ec14_1
widgetsnbextension 3.1.4 py36_0
win_inet_pton 1.0.1 py36he67d7fd_1
wincertstore 0.2 py36h7fe50ca_0
winpty 0.4.3 4
wrapt 1.10.11 py36he5f5981_0
yaml 0.1.7 hc54c509_2
zlib 1.2.11 h8395fce_2
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