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GitHub / UPstartDeveloper / electricity-consumption-regression

Building a deep learning model to predict the consumption of electricity. Data is from Kaggle: https://www.kaggle.com/utathya/notebook?select=train.csv

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UPstartDeveloper%2Felectricity-consumption-regression

Stars: 0
Forks: 0
Open Issues: 17

License: mit
Language: Jupyter Notebook
Repo Size: 534 KB
Dependencies: 90

Created: almost 4 years ago
Updated: almost 3 years ago
Last pushed: over 1 year ago
Last synced: about 1 year ago

Files

Readme

Dependencies

requirements.txt pypi

Jinja2 ==2.11.2
Keras ==2.4.2
Keras-Preprocessing ==1.1.2
Markdown ==3.2.2
MarkupSafe ==1.1.1
PyYAML ==5.3.1
Pygments ==2.6.1
Send2Trash ==1.5.0
Werkzeug ==1.0.1
absl-py ==0.9.0
appnope ==0.1.0
astunparse ==1.6.3
attrs ==19.3.0
backcall ==0.2.0
bleach ==3.1.5
cachetools ==4.1.0
certifi ==2020.6.20
chardet ==3.0.4
cycler ==0.10.0
decorator ==4.4.2
defusedxml ==0.6.0
entrypoints ==0.3
gast ==0.3.3
google-auth ==1.18.0
google-auth-oauthlib ==0.4.1
google-pasta ==0.2.0
grpcio ==1.29.0
h5py ==2.10.0
idna ==2.9
importlib-metadata ==1.6.1
ipykernel ==5.3.0
ipython ==7.15.0
ipython-genutils ==0.2.0
jedi ==0.17.1
joblib ==0.15.1
json5 ==0.9.5
jsonschema ==3.2.0
jupyter-client ==6.1.3
jupyter-core ==4.6.3
jupyterlab ==2.1.4
jupyterlab-server ==1.1.5
kiwisolver ==1.2.0
matplotlib ==3.2.2
mistune ==0.8.4
nbconvert ==5.6.1
nbformat ==5.0.7
notebook ==6.0.3
numpy ==1.19.0
oauthlib ==3.1.0
opt-einsum ==3.2.1
packaging ==20.4
pandas ==1.0.5
pandocfilters ==1.4.2
parso ==0.7.0
pexpect ==4.8.0
pickleshare ==0.7.5
prometheus-client ==0.8.0
prompt-toolkit ==3.0.5
protobuf ==3.12.2
ptyprocess ==0.6.0
pyasn1 ==0.4.8
pyasn1-modules ==0.2.8
pyparsing ==2.4.7
pyrsistent ==0.16.0
python-dateutil ==2.8.1
pytz ==2020.1
pyzmq ==19.0.1
requests ==2.24.0
requests-oauthlib ==1.3.0
rsa ==4.6
scikit-learn ==0.23.1
scipy ==1.4.1
seaborn ==0.10.1
six ==1.15.0
sklearn ==0.0
tensorboard ==2.2.2
tensorboard-plugin-wit ==1.6.0.post3
tensorflow ==2.5.0
tensorflow-estimator ==2.2.0
termcolor ==1.1.0
terminado ==0.8.3
testpath ==0.4.4
threadpoolctl ==2.1.0
tornado ==6.0.4
traitlets ==4.3.3
urllib3 ==1.25.9
wcwidth ==0.2.4
webencodings ==0.5.1
wrapt ==1.12.1
zipp ==3.1.0