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requirements.txt
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joblib
# swiftapply for speeding up pandas apply operations
swifter
#jupyter plugin
wurlitzer
# dimensionality
#-e [email protected]:DmitryUlyanov/Multicore-TSNE.git#egg=Multicore-TSNE
cython
# OR tools
ortools
# progress bar library for python and jupyter notebook
tqdm
# Visualization packages
bokeh==0.10.0
seaborn
matplotlib
# shapely
hypertools # For multi-dimensional data
astropy
patsy
# Modular data processing
mdp
#Meta learning
auto-sklearn
optunity
# Vision
scikit-image
#Satellite imagery
descartes
# Stats Packages
statsmodels
# Feature selector for timeseries
tsfresh
#Forecasting for timeseries
#fbprophet
# Genetic algo based feature selection
# Tools for tpot
deap
update_checker
# Automated sklearn
tpot
-e git+https://github.com/hyperopt/hyperopt-sklearn.git#egg=hpsklearn
# notebook tools
jupyter
psycopg2
# matrix tool + data structure/frame
numpy
pandas
sqlalchemy
scikit-learn
scipy
scikit-plot
#Non-linear correlation measures
ace
#Xtreme Gradient Boosting
xgboost
#Rasterio reads and writes geospatial raster datasets
rasterio
# NLP stuff
#nltk
#gensim
#glove
#Light GBM
#-e git+https://github.com/Microsoft/LightGBM.git#egg=lightgbm
-e git+https://github.com/ArdalanM/pyLightGBM.git#egg=pylightgbm
# Manifold learning
# -e git+https://github.com/lmcinnes/umap.git#egg=umap
# Package for map projections
geos
#Scikits-plugins
#scikit-beam
scikit-MDR
scikit-build
#scikit-cuda
scikit-data
# Goodness of fit tests
scikit-gof
# Geodesic manifolds
#scikit-geodesic
#scikit-gpuppy
#scikit-kinematics
#scikit-multilearn
scikit-neuralnetwork
#scikit-procrustes
#scikit-sound
#scikit-sos
#scikit-xray
#datasmooth
#scikits.talkbox
# Neural network packages
tensorflow
gym
keras
mxnet
tensorboard
-e git+https://github.com/sevamoo/SOMPY#egg=sompy
neat-python
# Vision packages
#object detections
#gpod
#Workflow management
#dagpype
#luigi
# String fuzzy(lev. distance based) matching
fuzzywuzzy
# Faster Text search
flashtext
#datarobot
#pynasa
# For graphical models
#pystruct
#seqlearn
# For recommendation engines
#scikit-surprise
# For understanding blackbox models
#skater
# Pygraphistry for visualizing large graphs
#graphistry[all]
#vispy
#For message passing across processes
#mpi4py
# Ipython volume
ipyvolume
pymc
causality