ml-finance-python
python scripts for finance machine learning
git clone https://9o.is/git/ml-finance-python.git
environment.yml
(4408B)
1 name: ml4t
2 channels:
3 - pytorch
4 - conda-forge
5 - defaults
6 dependencies:
7 - beautifulsoup4=4.6.3
8 - bottleneck=1.2.1
9 - cloudpickle=0.6.1
10 - colorlover=0.2.1
11 - cytoolz=0.9.0.1
12 - dask-core=1.0.0
13 - empyrical=0.3.4
14 - entrypoints=0.2.3
15 - fribidi=1.0.5
16 - graphite2=1.3.13
17 - harfbuzz=1.9.0
18 - imageio=2.4.1
19 - ipydatawidgets=4.0.0
20 - ipyscales=0.3.0
21 - ipyvolume=0.5.1
22 - ipywebrtc=0.4.3
23 - jupyter_contrib_core=0.3.3
24 - jupyter_contrib_nbextensions=0.5.0
25 - jupyter_highlight_selected_word=0.2.0
26 - jupyter_latex_envs=1.4.4
27 - jupyter_nbextensions_configurator=0.4.0
28 - libxslt=1.1.32
29 - networkx=2.2
30 - pexpect=4.6.0
31 - pixman=0.34.0
32 - ptyprocess=0.6.0
33 - pyopenssl=18.0.0
34 - python-graphviz=0.8.4
35 - pythreejs=2.0.2
36 - pywavelets=1.0.1
37 - pyyaml=3.13
38 - scikit-image=0.14.1
39 - setuptools=40.6.3
40 - terminado=0.8.1
41 - toolz=0.9.0
42 - traitlets=4.3.2
43 - traittypes=0.2.1
44 - umap-learn=0.3.7
45 - wheel=0.32.3
46 - yaml=0.1.7
47 - arrow-cpp=0.11.1
48 - asn1crypto=0.24.0
49 - atomicwrites=1.2.1
50 - attrs=18.2.0
51 - autopep8=1.4.3
52 - backcall=0.1.0
53 - binutils_impl_linux-64=2.28.1
54 - binutils_linux-64=7.2.0
55 - blas=1.0
56 - bleach=3.0.2
57 - blosc=1.14.4
58 - bokeh=1.0.2
59 - boto=2.49.0
60 - boto3=1.9.66
61 - botocore=1.12.67
62 - bzip2=1.0.6
63 - ca-certificates=2018.03.07
64 - cairo=1.14.12
65 - certifi=2018.11.29
66 - cffi=1.11.5
67 - chardet=3.0.4
68 - cryptography=2.4.2
69 - cycler=0.10.0
70 - dbus=1.13.2
71 - decorator=4.3.0
72 - docutils=0.14
73 - expat=2.2.6
74 - fastparquet=0.1.6
75 - fontconfig=2.13.0
76 - freetype=2.9.1
77 - gcc_impl_linux-64=7.2.0
78 - gcc_linux-64=7.2.0
79 - gflags=2.2.2
80 - glib=2.56.2
81 - glog=0.3.5
82 - gmp=6.1.2
83 - graphviz=2.40.1
84 - gst-plugins-base=1.14.0
85 - gstreamer=1.14.0
86 - gxx_impl_linux-64=7.2.0
87 - gxx_linux-64=7.2.0
88 - h5py=2.9.0
89 - hdf5=1.10.4
90 - html5lib=1.0.1
91 - icu=58.2
92 - idna=2.8
93 - inflection=0.3.1
94 - intel-openmp=2019.1
95 - ipykernel=5.1.0
96 - ipython=7.2.0
97 - ipython_genutils=0.2.0
98 - ipywidgets=7.4.2
99 - jedi=0.13.2
100 - jinja2=2.10
101 - jmespath=0.9.3
102 - joblib=0.13.0
103 - jpeg=9b
104 - jsonschema=2.6.0
105 - jupyter=1.0.0
106 - jupyter_client=5.2.4
107 - jupyter_console=6.0.0
108 - jupyter_core=4.4.0
109 - kiwisolver=1.0.1
110 - libboost=1.67.0
111 - libedit=3.1.20170329
112 - libevent=2.1.8
113 - libffi=3.2.1
114 - libgcc-ng=8.2.0
115 - libgfortran-ng=7.3.0
116 - libgpuarray=0.7.6
117 - libpng=1.6.35
118 - libsodium=1.0.16
119 - libstdcxx-ng=8.2.0
120 - libtiff=4.0.9
121 - libuuid=1.0.3
122 - libxcb=1.13
123 - libxml2=2.9.8
124 - lightgbm=2.2.1
125 - llvmlite=0.26.0
126 - lxml=4.2.5
127 - lz4-c=1.8.1.2
128 - lzo=2.10
129 - mako=1.0.7
130 - markupsafe=1.1.0
131 - matplotlib=3.0.2
132 - mistune=0.8.4
133 - mkl=2019.1
134 - mkl-service=1.1.2
135 - mkl_fft=1.0.6
136 - mkl_random=1.0.2
137 - more-itertools=4.3.0
138 - nbconvert=5.3.1
139 - nbformat=4.4.0
140 - ncurses=6.1
141 - ninja=1.8.2
142 - nltk=3.4
143 - notebook=5.7.4
144 - numba=0.41.0
145 - numexpr=2.6.8
146 - numpy=1.15.4
147 - numpy-base=1.15.4
148 - olefile=0.46
149 - openssl=1.1.1a
150 - packaging=18.0
151 - pandas=0.23.4
152 - pandas-datareader=0.7.0
153 - pandoc=2.2.3.2
154 - pandocfilters=1.4.2
155 - pango=1.42.4
156 - parso=0.3.1
157 - patsy=0.5.1
158 - pcre=8.42
159 - pickleshare=0.7.5
160 - pillow=5.3.0
161 - pip=18.1
162 - plotly=3.4.2
163 - pluggy=0.8.0
164 - prometheus_client=0.5.0
165 - prompt_toolkit=2.0.7
166 - py=1.7.0
167 - pyarrow=0.11.1
168 - pycodestyle=2.4.0
169 - pycparser=2.19
170 - pygments=2.3.1
171 - pygpu=0.7.6
172 - pymc3=3.5
173 - pyparsing=2.3.0
174 - pyqt=5.9.2
175 - pysocks=1.6.8
176 - pytables=3.4.4
177 - pytest=4.0.2
178 - python-dateutil=2.7.5
179 - pytz=2018.7
180 - pyzmq=17.1.2
181 - qt=5.9.7
182 - qtconsole=4.4.3
183 - quandl=3.4.5
184 - readline=7.0
185 - requests=2.21.0
186 - retrying=1.3.3
187 - s3transfer=0.1.13
188 - scikit-learn=0.20.1
189 - scipy=1.1.0
190 - seaborn=0.9.0
191 - send2trash=1.5.0
192 - sip=4.19.8
193 - six=1.12.0
194 - smart_open=1.7.1
195 - snappy=1.1.7
196 - sqlite=3.26.0
197 - statsmodels=0.9.0
198 - testpath=0.4.2
199 - theano=1.0.2
200 - thrift=0.11.0
201 - thrift-cpp=0.11.0
202 - tk=8.6.8
203 - tornado=5.1.1
204 - tqdm=4.28.1
205 - urllib3=1.24.1
206 - wcwidth=0.1.7
207 - webencodings=0.5.1
208 - widgetsnbextension=3.4.2
209 - wrapt=1.10.11
210 - xlrd=1.2.0
211 - xz=5.2.4
212 - zeromq=4.2.5
213 - zlib=1.2.11
214 - zstd=1.3.3
215 - pytorch=1.0.0
216 - torchvision=0.2.1
217 - pip:
218 - bz2file==0.98
219 - cython==0.29.2
220 - dask==1.0.0
221 - gensim==3.6.0
222 - hdbscan==0.8.18
223 - pyfinance==1.1.1
224 - tables==3.4.4
225 - torch==1.0.0
226 - xmltodict==0.11.0